{"id":"W6982072752","doi":"","title":"Grants Germaine Cousin","year":2014,"lang":"fr","type":"other","venue":"Persée (Ministère de lEnseignement supérieur et de la Recherche)","topic":"Pharmacology and Nanomedicine Research","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cousin; Work (physics); Quarter (Canadian coin); Inheritance (genetic algorithm)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.0295231,0.00167207,0.00190492,0.0008480852,0.000780348,0.000143303,0.00175626,0.008164744,0.1344526],"category_scores_gemma":[0.003781379,0.001776102,0.0007143841,0.0008402482,0.002987959,0.000152571,0.0005635215,0.01350492,0.004412072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003374153,"about_ca_system_score_gemma":0.004690278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008022608,"about_ca_topic_score_gemma":0.0006764185,"domain_scores_codex":[0.9538634,0.03895717,0.001372331,0.001700137,0.0008239106,0.003283088],"domain_scores_gemma":[0.97704,0.01924558,0.0007018888,0.0009742251,0.0003249095,0.001713374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003189972,0.004288773,0.00568043,0.00252681,0.003677404,0.004108047,0.08954314,0.0001759039,0.1040904,0.007719813,0.7175205,0.05747889],"study_design_scores_gemma":[0.008196479,0.001004781,0.002040535,0.0004617152,0.001711969,0.0008881338,0.001028149,0.003307162,0.006782765,0.002197684,0.9708272,0.001553422],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1440791,0.01410172,0.003513777,0.03234953,0.003161033,0.002973518,0.0006203259,0.0005622139,0.7986388],"genre_scores_gemma":[0.2490115,0.03485789,0.004787497,0.0511957,0.004297921,0.0008906415,0.0005697153,0.001093186,0.653296],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2533067,"threshold_uncertainty_score":0.9997253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1651646453265964,"score_gpt":0.4755635986141509,"score_spread":0.3103989532875545,"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."}}