{"id":"W2917105194","doi":"10.1002/ece3.4740","title":"A comparison of techniques for classifying behavior from accelerometers for two species of seabird","year":2019,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Environment and Climate Change Canada; Ste. Anne's Hospital","funders":"University of Manitoba; Natural Sciences and Engineering Research Council of Canada; McGill University; British Ornithologists' Union","keywords":"Seabird; Accelerometer; Animal behavior; Ecology; Biology; Computer science; Artificial intelligence; Zoology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002409036,0.0008460218,0.0003823885,0.001784013,0.0002676981,0.0005985504,0.0006975826,0.0006921343,0.0007734811],"category_scores_gemma":[0.007947312,0.0002458209,0.0003943079,0.0007723067,0.0002346834,0.0006434332,0.0005642645,0.000318012,0.0005259775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003184978,"about_ca_system_score_gemma":0.0002015923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002454397,"about_ca_topic_score_gemma":0.004909869,"domain_scores_codex":[0.9980197,0.0007385391,0.0002350569,0.0003601426,0.0005485894,0.00009793192],"domain_scores_gemma":[0.9896675,0.00487488,0.001269393,0.0005521364,0.003391554,0.0002445725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001981069,0.0003898498,0.3661838,0.0005390081,0.0005848043,0.00007560143,0.0006608816,0.007915802,0.08894917,0.0002238668,0.001489281,0.5310068],"study_design_scores_gemma":[0.0001493118,0.001663219,0.6563714,0.0001271248,0.0003644318,0.0004694084,0.0008188686,0.2995615,0.03772854,0.0004691552,0.002129418,0.000147641],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8731598,0.0007888227,0.1229146,0.0001449524,0.0001262798,0.000222016,0.0004813016,0.0007942021,0.001367954],"genre_scores_gemma":[0.8615299,0.0002933636,0.1367505,0.00005546827,0.00004580728,0.0001332781,0.0004567504,0.00004735755,0.0006876126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002454397,"threshold_uncertainty_score":0.01274037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03865603506016397,"score_gpt":0.3108423900289292,"score_spread":0.2721863549687653,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}