InsectNet v0.1.0

InsectNet v0.1.0 is a preserved research classifier for scoring insect- and amphibian-related acoustic classes from frozen BirdNET v2.4 output logits.

This Hugging Face repository is the model-release mirror. The canonical source, tests, package, and GitHub Release are at github.com/vortexpjeff/insectnet.

This repository intentionally contains one model artifact and one release identity. It does not publish live sensor addresses, deployment credentials, exact collection locations, private media, or an unattended capture service.

Release identity

Release:  insectnet-v0.1.0
Artifact: classifier.joblib
SHA-256: 5e6ecfc68d78a2cf2e9e9e47da5cb58d696e8de354fd620cfcccc5db9da48702
Bytes:    474,892
Status:   historical research reference

The artifact is byte-for-byte preserved from the original v0.1 field prototype.

Model contract

Audio window:       3.0 seconds
Sample rate:        48,000 Hz mono
Backbone:           BirdNET v2.4 FP16 TFLite
Feature space:      6,522 BirdNET output logits
Classifier:         StandardScaler → OneVsRest LogisticRegression
Serialization:      scikit-learn 1.8.0
Output semantics:   independent per-class probabilities

Class order:

background
bee
cicada_drone
cricket_katydid
frog
grasshopper

The model file does not embed thresholds, a version number, or its original training snapshot. Those omissions are part of the preserved v0.1 record rather than silently reconstructed metadata.

What is included

the exact v0.1 model artifact;
a machine-readable release manifest;
artifact and feature-contract verification;
offline scoring for precomputed BirdNET logit vectors;
tests that enforce the model checksum, class order, feature dimension, and public privacy boundary;
documented provenance and limitations.

What is not included

live capture or sensor-watching code;
deployment scripts;
device addresses or credentials;
exact collection locations;
raw or private field audio;
later experimental model candidates;
claims of production readiness.

The original live sidecar diverged from the public v0.1 source during field experiments. That runtime is not republished here until it can be recovered, tested, and released under a separate reviewed version.

Verify the preserved artifact

From a source checkout:

uv run insectnet verify

Expected SHA-256:

5e6ecfc68d78a2cf2e9e9e47da5cb58d696e8de354fd620cfcccc5db9da48702

Score precomputed logits

InsectNet v0.1 expects one finite NumPy vector with shape (6522,) extracted from the declared BirdNET backbone:

uv run insectnet score logits.npy

The command returns one probability per declared class. These scores are model assertions for review, not confirmed biological observations.

Joblib safety: joblib artifacts use Python pickle internally. Load only the artifact whose checksum matches the release manifest.

Known limitations

Later audits found high false-positive rates on some bird vocalizations.
Bee and grasshopper had limited training coverage.
The surviving metrics came from limited public-data evaluation and one private field site; they do not establish general production performance.
Exact reproduction is blocked because the original per-record training snapshot is unavailable.
The classifier relies on BirdNET logits and cannot score raw audio by itself.
There is no validated automated-decision threshold policy in this release.

Provenance

The surviving records identify these source families:

InsectSet459: current dataset card states CC BY 4.0, with some source material CC0.
ESC-50: CC BY-NC 3.0.
iNaturalist audio: licenses vary per recording; the original per-record manifest is unavailable.
Private field negatives: not redistributed.

See PROVENANCE.md and the release manifest for the exact surviving claims and gaps.

Privacy and security

The public release intentionally omits exact collection location, network topology, account names, credentials, private paths, and raw evidence. See SECURITY_AND_PRIVACY.md.

License

The repository and preserved release are distributed under CC BY-NC-SA 4.0, subject to the licenses and terms of the upstream backbone and source media. Source-media rights vary; users are responsible for reviewing those upstream terms for their use case.

This provenance statement is not legal advice.

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