{"id":"W2056166168","doi":"10.1163/156853907782418213","title":"A maximum likelihood approach for identifying dive bouts improves accuracy, precision and objectivity","year":2007,"lang":"en","type":"article","venue":"Behaviour","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Shandong Academy of Sciences; Institut Polaire Français Paul Emile Victor","keywords":"Bin; Maximum likelihood; Computer science; Foraging; Statistics; Artificial intelligence; Machine learning; Mathematics; Ecology; Algorithm; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.006973434,0.0007046118,0.0009360848,0.001946041,0.0004766131,0.001475147,0.0009490009,0.001237391,0.001348231],"category_scores_gemma":[0.02821594,0.0006335555,0.0009865251,0.001001604,0.0007678889,0.001715401,0.001463865,0.001093649,0.0003877839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006385049,"about_ca_system_score_gemma":0.0008073139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003116652,"about_ca_topic_score_gemma":0.003548642,"domain_scores_codex":[0.9967132,0.002017329,0.0002244491,0.0005317377,0.0004262425,0.00008713422],"domain_scores_gemma":[0.9819104,0.01502768,0.001047891,0.001040176,0.0008390573,0.0001348649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007459479,0.0003186943,0.08360294,0.0005019275,0.0006686088,0.0002962325,0.0006792733,0.3794563,0.02285594,0.01233813,0.001228343,0.4973077],"study_design_scores_gemma":[0.00002722145,0.0001181819,0.01449833,0.00004139745,0.0000515557,0.0001464133,0.00006839426,0.9745849,0.002998863,0.006604956,0.0008166645,0.00004312141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06870961,0.0002772094,0.9293751,0.0001785172,0.000015874,0.00004387043,0.00006851133,0.0005657384,0.0007655842],"genre_scores_gemma":[0.5459743,0.0001302892,0.4527069,0.00005685663,0.00003552952,0.0001316067,0.0001236403,0.00009994202,0.0007410728],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006973434,"threshold_uncertainty_score":0.03687948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03228370582213296,"score_gpt":0.2953883828139393,"score_spread":0.2631046769918063,"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."}}