{"id":"W4293810860","doi":"10.4000/adsc.773","title":"Didactique, sémantique et métaphores : analyse de langages en classe de géométrie","year":2016,"lang":"en","type":"article","venue":"Annales de didactique et de sciences cognitives","topic":"French Language Learning Methods","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Context (archaeology); Class (philosophy); Symmetry (geometry); Semantics (computer science); Pragmatics; Epistemology; Sociology; Mathematics education; Psychology; Linguistics; Computer science; Mathematics; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0167764,0.000340343,0.0003837547,0.0004629595,0.0008313,0.0005153726,0.0009837894,0.0003727984,0.0004223499],"category_scores_gemma":[0.02059549,0.0002679238,0.000237514,0.001054022,0.001962175,0.001309903,0.0001520931,0.0007446668,0.00005151314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004290026,"about_ca_system_score_gemma":0.003922464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0044048,"about_ca_topic_score_gemma":0.01050642,"domain_scores_codex":[0.9869829,0.009884269,0.0003455733,0.000709399,0.0006564033,0.001421393],"domain_scores_gemma":[0.9896928,0.008953672,0.0003081056,0.0002756775,0.0002710816,0.0004986296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001436467,0.0003576394,0.4968887,0.00006567077,0.0002338513,0.000576814,0.2737887,0.00008346938,0.09936164,0.04999865,0.004023201,0.07447807],"study_design_scores_gemma":[0.0008349031,0.0004736324,0.7409908,0.0007506043,0.0001473583,0.0001395162,0.07935208,0.0001960675,0.08826546,0.03631279,0.05120492,0.001331839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8899798,0.0009348533,0.03103602,0.01610815,0.0001184767,0.0002894187,0.0000325796,0.0003521683,0.06114852],"genre_scores_gemma":[0.961477,0.003287691,0.02766399,0.004107489,0.0002969543,0.00007673402,0.00000504341,0.00003913242,0.003045943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2441021,"threshold_uncertainty_score":0.9999773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03705867908203481,"score_gpt":0.42338889446211,"score_spread":0.3863302153800752,"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."}}