{"id":"W2613795649","doi":"10.7202/1038375ar","title":"Une approche textométrique pour étudier la transmission des savoirs biologiques au XIXe siècle","year":2016,"lang":"fr","type":"article","venue":"Nouvelles perspectives en sciences sociales","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Humanities; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.007257835,0.001475603,0.001050826,0.0115264,0.001829247,0.00890137,0.001571837,0.002182874,0.01588819],"category_scores_gemma":[0.03402397,0.0008903281,0.001327477,0.01075537,0.001312464,0.006648931,0.002995031,0.001897281,0.007234342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0014283,"about_ca_system_score_gemma":0.003069944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006724168,"about_ca_topic_score_gemma":0.008473982,"domain_scores_codex":[0.9941682,0.00201979,0.0007147293,0.001142306,0.001794235,0.0001608197],"domain_scores_gemma":[0.9760755,0.01350881,0.001200906,0.003225651,0.005702875,0.000286165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007254349,0.0001608049,0.02293319,0.004903537,0.0004516665,0.0009353615,0.02529398,0.006260714,0.06045683,0.053503,0.03566164,0.7887138],"study_design_scores_gemma":[0.0001461099,0.000276463,0.04880338,0.002511333,0.0005937002,0.002672733,0.02513102,0.08260117,0.05957974,0.08971608,0.6875228,0.0004453522],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0448648,0.002361231,0.8931758,0.003672254,0.0007627022,0.0009276523,0.01590123,0.01053704,0.02779721],"genre_scores_gemma":[0.1272815,0.001630999,0.8411525,0.0004000737,0.0002486023,0.00177249,0.009625413,0.002703402,0.01518502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9884736,"threshold_uncertainty_score":0.05315125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2232266220467862,"score_gpt":0.365910056307187,"score_spread":0.1426834342604008,"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."}}