{"id":"W2737315116","doi":"10.7202/1040377ar","title":"L’apport de François Beaudin : la mise en place du rapport Deschênes","year":2017,"lang":"fr","type":"article","venue":"Archives","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Université de Montréal","keywords":"Humanities; Political science; Art","routes":{"ca_aff":true,"ca_fund":true,"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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003768262,0.000298734,0.0002844039,0.00006272627,0.000706618,0.002658359,0.001336279,0.0001073252,0.0000643813],"category_scores_gemma":[0.000350552,0.0002395017,0.0001992373,0.00006041696,0.0007288234,0.00289022,0.0007812653,0.0002567391,0.0001597151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000175601,"about_ca_system_score_gemma":0.000397071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009238495,"about_ca_topic_score_gemma":0.0001242955,"domain_scores_codex":[0.9982082,0.0001850644,0.00026945,0.0004718134,0.0002143153,0.0006511032],"domain_scores_gemma":[0.9978493,0.0004719939,0.0002204206,0.0009149609,0.00003577593,0.0005074958],"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":[0.0001109247,0.0007035075,0.0245587,0.0002066842,0.0002467619,0.003840661,0.1125512,0.0001401994,0.005854065,0.2091291,0.1665283,0.4761299],"study_design_scores_gemma":[0.0005912049,0.0001593695,0.1758782,0.0002448868,0.00003471839,0.0008206375,0.0002633696,0.005060247,0.002445203,0.03975893,0.7742384,0.0005047933],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.295012,0.00274261,0.01057967,0.02544193,0.001171886,0.0002563253,0.00003275932,0.0001405861,0.6646222],"genre_scores_gemma":[0.7936699,0.0008971727,0.006073839,0.0005601378,0.000512608,0.000008998442,0.000006222239,0.00002068869,0.1982505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6077101,"threshold_uncertainty_score":0.998377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1579950527819639,"score_gpt":0.3001974748474651,"score_spread":0.1422024220655011,"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."}}