{"id":"W2261337710","doi":"10.7202/1029047ar","title":"Caractéristiques de schémas de classification personnels des documents administratifs électroniques : éléments d’analyse et de discussion","year":2015,"lang":"fr","type":"article","venue":"Documentation et bibliothèques","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Political science; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.008684396,0.0005338134,0.000472765,0.002699017,0.0004608293,0.01153243,0.0008649721,0.0003096343,0.003735867],"category_scores_gemma":[0.001085889,0.0004351092,0.0002825861,0.003368644,0.0003644578,0.02679965,0.0002026452,0.0004917629,0.0003543395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002952882,"about_ca_system_score_gemma":0.002514178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003820843,"about_ca_topic_score_gemma":0.001128843,"domain_scores_codex":[0.9927657,0.002374029,0.00129006,0.0007064794,0.001853966,0.001009748],"domain_scores_gemma":[0.9964789,0.0004282068,0.0009078825,0.0005507543,0.0007958738,0.0008383688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007069492,0.001390653,0.537272,0.0002339922,0.000381006,0.00007480816,0.1241843,0.000599436,0.006338092,0.076176,0.2082469,0.04439583],"study_design_scores_gemma":[0.003693573,0.001411084,0.4841673,0.0007980536,0.0008148715,0.0001120161,0.09832334,0.01715025,0.01656291,0.1421091,0.2329911,0.001866297],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8364967,0.003504344,0.09734455,0.02041655,0.0006592394,0.001055174,0.0001782878,0.0004094876,0.03993571],"genre_scores_gemma":[0.9274817,0.008095336,0.02221759,0.004116098,0.0001927258,0.0002018474,0.0003123992,0.00005264042,0.0373297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09098502,"threshold_uncertainty_score":0.99981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2341066842536733,"score_gpt":0.4985284522506283,"score_spread":0.264421767996955,"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."}}