{"id":"W2743293615","doi":"10.1242/bio.027029","title":"On the utility of accelerometers to predict stroke rate using captive fur seals and sea lions","year":2017,"lang":"en","type":"article","venue":"Biology Open","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Australian Research Council; Macquarie University","keywords":"Biology; Accelerometer; Stroke (engine); Fishery; Physical medicine and rehabilitation; Zoology; Computer science; Engineering; Aerospace engineering; Medicine","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":[0.001101503,0.000981493,0.000544527,0.001003252,0.0002159737,0.0006593114,0.0005695769,0.0006212383,0.0007775568],"category_scores_gemma":[0.003251435,0.0003421184,0.0003848625,0.0003861849,0.0002261071,0.0005173637,0.0003937844,0.0003149888,0.0004966437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002104943,"about_ca_system_score_gemma":0.000178981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005469218,"about_ca_topic_score_gemma":0.01162379,"domain_scores_codex":[0.9996316,0.0001057259,0.00002389115,0.0001337116,0.00007269422,0.00003241462],"domain_scores_gemma":[0.9989483,0.0004698678,0.000194496,0.00007281703,0.0002470259,0.00006762005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001244264,0.0001766046,0.8135927,0.0002747321,0.0004634557,0.0003502839,0.001272186,0.01019899,0.06720989,0.0001108157,0.0007950217,0.1043111],"study_design_scores_gemma":[0.00002662653,0.001104675,0.9381601,0.0001189467,0.0001780717,0.0003844588,0.0005991359,0.05100124,0.007344243,0.0001374317,0.0008841006,0.00006106038],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893265,0.0006037773,0.008575271,0.00004869836,0.00003245774,0.0000434316,0.0004120801,0.0001203169,0.0008374172],"genre_scores_gemma":[0.9827667,0.0005202738,0.01471958,0.00006760178,0.00004020378,0.000114744,0.0009356358,0.00002503614,0.0008102047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005469218,"threshold_uncertainty_score":0.01087475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1365414621933647,"score_gpt":0.3481413363614403,"score_spread":0.2115998741680757,"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."}}