{"id":"W7070414562","doi":"","title":"Objectif Numérique S01E53 - Le syndrôme de Stéphane","year":2014,"lang":"fr","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Panorama; Photography; Digital photography","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":[0.002387868,0.0006900829,0.0004680237,0.001767406,0.002070579,0.003587538,0.001719289,0.00455631,0.2079558],"category_scores_gemma":[0.02097398,0.0002600771,0.0005120934,0.0009411953,0.001839597,0.002358487,0.002750219,0.003405192,0.09579737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004401065,"about_ca_system_score_gemma":0.003335975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02314917,"about_ca_topic_score_gemma":0.02335798,"domain_scores_codex":[0.9974138,0.0004467588,0.0001640542,0.0002261118,0.001584559,0.0001647014],"domain_scores_gemma":[0.9918025,0.002199001,0.0004277618,0.0008128238,0.004318003,0.0004399155],"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":[0.00001044389,0.000004607796,0.0001246305,0.00007215708,0.000001366781,0.0001097731,0.0001444005,0.00001601572,0.00009770024,0.01093765,0.9679593,0.02052201],"study_design_scores_gemma":[0.000001819941,0.000002354197,0.0002001509,0.00009732675,0.00000100412,0.0002462103,0.00009935298,0.00001856387,0.0001046052,0.0009249229,0.9982998,0.000003918156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001146906,0.00425851,0.00526935,0.1647874,0.04238497,0.0002307751,0.003151415,0.001591452,0.7771792],"genre_scores_gemma":[0.01050944,0.002842853,0.00342227,0.02559295,0.006680724,0.0002403787,0.001948284,0.0007943177,0.9479689],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2079558,"threshold_uncertainty_score":0.6956815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002829108220727119,"score_gpt":0.1825724155806465,"score_spread":0.1797433073599193,"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."}}