{"id":"W3086157337","doi":"10.1007/s42330-020-00102-w","title":"Relations entre contexte, situation et schéma de résolution dans les problèmes d’estimation","year":2020,"lang":"fr","type":"article","venue":"Canadian Journal of Science Mathematics and Technology Education","topic":"Mathematics Education and Teaching Techniques","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Sequence (biology); Estimation; Context (archaeology); Task (project management); Word problem (mathematics education); Word (group theory); Computer science; Scheme (mathematics); Flexibility (engineering); Mathematics; Artificial intelligence; Arithmetic; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.02049358,0.001155076,0.001098917,0.004292897,0.002444311,0.01185344,0.002357506,0.003294592,0.007452809],"category_scores_gemma":[0.1059386,0.001517159,0.00198163,0.004389149,0.004760208,0.01590987,0.003353686,0.003786824,0.0007700844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003635075,"about_ca_system_score_gemma":0.004293913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02969537,"about_ca_topic_score_gemma":0.01520518,"domain_scores_codex":[0.9659164,0.02145965,0.002950779,0.003473502,0.005317615,0.0008821353],"domain_scores_gemma":[0.9234605,0.06606432,0.00222513,0.003684558,0.00418197,0.0003834224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001084697,0.0002356346,0.05632615,0.001539303,0.0006223119,0.002192095,0.02537154,0.03545268,0.00427602,0.6577198,0.004072459,0.2111074],"study_design_scores_gemma":[0.0002870278,0.0002990247,0.02974231,0.001496965,0.0007417006,0.004518082,0.03152976,0.3084278,0.01603438,0.5315704,0.07495811,0.0003944695],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1317934,0.003132045,0.8373468,0.008478118,0.0002072556,0.0002556372,0.0008319804,0.0006551336,0.01729954],"genre_scores_gemma":[0.6544594,0.001475844,0.3395783,0.0002047255,0.0001006364,0.0002067698,0.001182151,0.0001595371,0.002632593],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02969537,"threshold_uncertainty_score":0.1083817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02768309507218483,"score_gpt":0.314684119516038,"score_spread":0.2870010244438531,"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."}}