{"id":"W3183582410","doi":"","title":"Can Children use Numerical Reasoning to Compare Odds in Games","year":2021,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Cognitive and developmental aspects of mathematical skills","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Odds; Game of chance; Set (abstract data type); Coin flipping; Simple (philosophy); Computer science; Psychology; Mathematics; Statistics; Machine learning; Logistic regression; Epistemology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.004413919,0.0008676705,0.0006205731,0.00119037,0.0002919935,0.004441081,0.0009973979,0.001152285,0.00404827],"category_scores_gemma":[0.05309246,0.0007030251,0.0009057261,0.0005297874,0.001774303,0.007093745,0.001708211,0.0009952537,0.001210433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005906705,"about_ca_system_score_gemma":0.000683502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004347729,"about_ca_topic_score_gemma":0.004377145,"domain_scores_codex":[0.9962683,0.001130332,0.0003823674,0.0008259562,0.00102597,0.0003669768],"domain_scores_gemma":[0.9811333,0.008837473,0.006325836,0.002069565,0.0008820863,0.0007518158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001336309,0.000865088,0.6577902,0.000697507,0.000476061,0.001243135,0.02739331,0.01240168,0.02383674,0.03023497,0.003765459,0.2399595],"study_design_scores_gemma":[0.0004694298,0.002123542,0.7640668,0.000833639,0.0005616597,0.002707355,0.02166662,0.05039467,0.02692952,0.1010485,0.02862899,0.0005693366],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671232,0.0003802311,0.009796535,0.0006126263,0.00003081439,0.00007011414,0.0001977305,0.0002218746,0.02156697],"genre_scores_gemma":[0.9864566,0.0002138064,0.01200668,0.00009655112,0.00000606817,0.00004211824,0.0002079074,0.00002249706,0.0009477467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004441081,"threshold_uncertainty_score":0.02334332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437326829280629,"score_gpt":0.2550287502990869,"score_spread":0.2306554820062807,"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."}}