{"id":"W1541355862","doi":"10.4000/contextes.1533","title":"Compte rendu de Lemercier (Claire) et Zalc (Claire), Méthodes quantitatives pour l’historien","year":2022,"lang":"fr","type":"article","venue":"Contextes","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"","keywords":"Art","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03648232,0.00115968,0.00113369,0.0104699,0.004531935,0.007813714,0.001222481,0.001920393,0.008769127],"category_scores_gemma":[0.1025795,0.000944769,0.001210339,0.00946395,0.006688024,0.006388532,0.004966285,0.005404462,0.00181116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01027841,"about_ca_system_score_gemma":0.01248722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06359193,"about_ca_topic_score_gemma":0.09036537,"domain_scores_codex":[0.9716021,0.01847723,0.001301042,0.002967828,0.005085932,0.0005658156],"domain_scores_gemma":[0.9406787,0.04195243,0.003417726,0.003973905,0.009519357,0.0004578906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002103853,0.0001089583,0.01064433,0.0034567,0.000341205,0.0001607138,0.07237279,0.001175221,0.003978204,0.4881223,0.05230134,0.3671279],"study_design_scores_gemma":[0.00007929645,0.000138743,0.03508362,0.004541549,0.0002441443,0.000235046,0.02092702,0.002742782,0.005473439,0.1428388,0.7874769,0.0002186879],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.07165484,0.09381711,0.5741188,0.06719362,0.004748395,0.003735537,0.007724853,0.001627177,0.1753797],"genre_scores_gemma":[0.3079584,0.02959364,0.5216252,0.01469239,0.0007676099,0.008417662,0.002127738,0.001373935,0.1134435],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.06359193,"threshold_uncertainty_score":0.1929392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06554172504456501,"score_gpt":0.3178585235523313,"score_spread":0.2523167985077663,"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."}}