{"id":"W7037303479","doi":"","title":"Enjeux et transformations de la société québécoise Issues and transformations of Quebecois society","year":2010,"lang":"fr","type":"other","venue":"OpenEdition (OpenEdition)","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Government (linguistics); Agency (philosophy); Perspective (graphical); Exposition (narrative)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003727671,0.0007651413,0.0009991929,0.0002932896,0.0009045862,0.0009770435,0.001016142,0.001072149,0.08520402],"category_scores_gemma":[0.0005826891,0.000784304,0.000346451,0.0004875147,0.002017869,0.01001273,0.0001555534,0.0009913001,0.001047535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002276431,"about_ca_system_score_gemma":0.001236772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005122939,"about_ca_topic_score_gemma":0.01676527,"domain_scores_codex":[0.9947163,0.001330891,0.001403967,0.0008277758,0.0009518125,0.0007692316],"domain_scores_gemma":[0.9964703,0.0009275685,0.001002872,0.0007018955,0.0005000526,0.0003973605],"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":[0.00008986887,0.0007684542,0.00008935737,0.002513144,0.0001549111,0.000009597671,0.01048869,0.002606536,0.2115781,0.7240517,0.03973144,0.007918268],"study_design_scores_gemma":[0.00237169,0.0003755784,0.01352705,0.001707089,0.0004995733,0.0002882348,0.001401902,0.003688735,0.0442653,0.01568263,0.9144192,0.00177298],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03357984,0.002085254,0.08178378,0.1212188,0.00657544,0.003854653,0.008275454,0.0006184994,0.7420082],"genre_scores_gemma":[0.3690079,0.02301573,0.3143114,0.05460237,0.004788907,0.002976326,0.006453005,0.001175922,0.2236685],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8746878,"threshold_uncertainty_score":0.9997303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01031728734314853,"score_gpt":0.2897144832277672,"score_spread":0.2793971958846186,"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."}}