{"id":"W2979144778","doi":"10.1071/aj09129","title":"Kipper-Tuna-Turrum","year":2010,"lang":"fr","type":"article","venue":"The APPEA Journal","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ARC Resources (Canada)","funders":"","keywords":"Tuna; Fishery; Biology; Fish <Actinopterygii>","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0023722,0.0002768914,0.000237539,0.00009389768,0.001079436,0.001521092,0.003336392,0.0002004885,0.002019149],"category_scores_gemma":[0.0003809723,0.0001914496,0.0002624309,0.0004468128,0.0008754249,0.001033632,0.0005757456,0.002819266,0.004803543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005110279,"about_ca_system_score_gemma":0.0003485555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000109223,"about_ca_topic_score_gemma":0.0001499105,"domain_scores_codex":[0.9972149,0.0003048621,0.000599285,0.0003184282,0.0006553985,0.0009071043],"domain_scores_gemma":[0.9976181,0.0003234188,0.0003407972,0.001022566,0.0003190747,0.0003760565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000149616,0.0001358387,0.0006011938,0.000009042445,0.00005818191,0.000212401,0.00598997,0.000228615,0.008507592,0.3187809,0.04193128,0.62353],"study_design_scores_gemma":[0.0001111161,0.0001567442,0.001115554,0.0001173568,0.00004206569,0.008176104,0.0005253593,0.03020922,0.01252173,0.1768496,0.7697794,0.0003957078],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2067763,0.01261517,0.3105751,0.3643641,0.06909394,0.0003768997,0.000006974967,0.0001653209,0.03602624],"genre_scores_gemma":[0.9476748,0.0006413518,0.01206961,0.003237877,0.008276602,0.00000432839,3.080203e-7,0.0000416471,0.02805349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7408985,"threshold_uncertainty_score":0.9995154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04579326281708071,"score_gpt":0.3023424895758868,"score_spread":0.2565492267588061,"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."}}