{"id":"W2122303322","doi":"10.1371/journal.pone.0077814","title":"Identification of Behaviour in Freely Moving Dogs (Canis familiaris) Using Inertial Sensors","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Human-Animal Interaction Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Ethogram; Accelerometer; Artificial intelligence; Identification (biology); Support vector machine; Ethology; Computer science; Gyroscope; Pattern recognition (psychology); Animal behavior; Robustness (evolution); Data collection; Machine learning; Computer vision; Mathematics; Statistics; Biology; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003551026,0.0003351047,0.00033246,0.0009852964,0.0001854836,0.0003005948,0.0003441924,0.0003553891,0.0004770313],"category_scores_gemma":[0.000691502,0.0002091567,0.0001531254,0.0004004215,0.0004595827,0.0003263984,0.0003706391,0.0001679619,0.0002563068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001999387,"about_ca_system_score_gemma":0.0001874128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004606274,"about_ca_topic_score_gemma":0.01050422,"domain_scores_codex":[0.9996884,0.00004393369,0.00001596905,0.0001686844,0.00004837806,0.00003464629],"domain_scores_gemma":[0.9996194,0.00007815102,0.0001504808,0.00003649889,0.0000659112,0.00004950239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005603447,0.0003193884,0.5631297,0.0002706631,0.0001205838,0.0005509641,0.001999853,0.001899911,0.3272118,0.0001548355,0.0005871696,0.1031947],"study_design_scores_gemma":[0.00001085308,0.0007458118,0.9859859,0.00002166485,0.00004463618,0.0006810578,0.0004055643,0.004341988,0.007006006,0.00005425029,0.0006807338,0.00002164003],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961349,0.0002378333,0.00311006,0.0000146294,0.000005927497,0.00002052913,0.0001693729,0.00005510015,0.0002516209],"genre_scores_gemma":[0.9874742,0.0002673273,0.01103484,0.00002793646,0.00001208813,0.00004955104,0.0005771666,0.00001051293,0.0005463305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004606274,"threshold_uncertainty_score":0.009158909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04167891930123541,"score_gpt":0.3051048421571371,"score_spread":0.2634259228559017,"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."}}