{"id":"W2943521459","doi":"10.4000/books.pressesenssib.6583","title":"Identifier des sources de financement : le cas de la médiathèque de Roubaix","year":2017,"lang":"fr","type":"book-chapter","venue":"","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Political science","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":[0.001361945,0.0005402829,0.0003389951,0.003016297,0.004858745,0.009954462,0.000797851,0.001629432,0.009807917],"category_scores_gemma":[0.002845217,0.0003749293,0.0002262145,0.003171846,0.006463266,0.007444348,0.003392734,0.002544514,0.001307302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00709905,"about_ca_system_score_gemma":0.00289854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02194477,"about_ca_topic_score_gemma":0.02753471,"domain_scores_codex":[0.9990768,0.0002535316,0.00001864047,0.0001306589,0.0003650722,0.0001552387],"domain_scores_gemma":[0.9993429,0.0003376592,0.00009179689,0.00006680512,0.0001029434,0.0000578789],"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":[0.0000307345,0.000008070342,0.0007836462,0.00005363642,0.000006136959,0.0003742618,0.01960041,0.0001585991,0.0002500304,0.9391322,0.009398479,0.03020392],"study_design_scores_gemma":[0.00001679142,0.00002690251,0.004090891,0.0004952065,0.00001823159,0.0009137734,0.01324445,0.0007965409,0.001237198,0.09109592,0.8880301,0.00003400887],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08100583,0.02104137,0.009286419,0.02037637,0.0007342908,0.00003827909,0.0001945725,0.0001287242,0.8671941],"genre_scores_gemma":[0.6300454,0.01183821,0.004813365,0.001022549,0.0006930508,0.0000551054,0.0001559134,0.0001842571,0.3511922],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02194477,"threshold_uncertainty_score":0.05150741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2372593102234476,"score_gpt":0.3303026072645123,"score_spread":0.09304329704106473,"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."}}