{"id":"W2097077063","doi":"10.1007/s00265-012-1414-4","title":"The recursive model as a new approach to validate and monitor activity sensors","year":2012,"lang":"en","type":"article","venue":"Behavioral Ecology and Sociobiology","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Concordia University","keywords":"Animal ecology; Tree (set theory); Logistic regression; Computer science; Data mining; Statistics; Decision tree; Machine learning; Mathematics; Artificial intelligence; Ecology; Biology","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":[0.002888151,0.0009549514,0.001206744,0.0006929348,0.0004658221,0.001757404,0.002520076,0.001599065,0.002768551],"category_scores_gemma":[0.01235092,0.000763472,0.001147068,0.0004673487,0.001394821,0.003439266,0.001601715,0.0022856,0.001005996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009216457,"about_ca_system_score_gemma":0.001718263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008465464,"about_ca_topic_score_gemma":0.008699402,"domain_scores_codex":[0.9978521,0.000854458,0.0001066676,0.0006199246,0.0004123386,0.0001545043],"domain_scores_gemma":[0.9938643,0.003997787,0.0004082281,0.0009258065,0.0007077437,0.00009604599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001112128,0.00008811879,0.00312566,0.00009282432,0.0001430928,0.0001102451,0.0001792034,0.8182678,0.008167084,0.1102948,0.0007680863,0.05865191],"study_design_scores_gemma":[0.000004855092,0.00002156989,0.0001552148,0.000005695406,0.0000153843,0.00002070616,0.000006061075,0.9868662,0.0009575525,0.01148985,0.0004468426,0.00001011486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003173582,0.00001834945,0.9960204,0.00003863966,0.000009623916,0.000009505708,0.00001953492,0.000223806,0.0004865278],"genre_scores_gemma":[0.4906873,0.0001471824,0.5035952,0.0001571174,0.00006197918,0.0002219405,0.0002510001,0.0003389373,0.00453945],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008465464,"threshold_uncertainty_score":0.01683241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1215420245174405,"score_gpt":0.3923919592910087,"score_spread":0.2708499347735682,"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."}}