{"id":"W3187054880","doi":"","title":"Plinko: A Theory-Free Behavioral Measure of Priors for Statistical Learning and Mental Model Updating.","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Prior probability; Bayesian probability; Artificial intelligence; Posterior probability; Bayesian inference; Computer science; Measure (data warehouse); Task (project management); Probability distribution; Machine learning; Psychology; Cognitive psychology; Mathematics; Statistics; Data mining","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":[0.01236776,0.001149381,0.0006290672,0.002767396,0.0007040325,0.002741913,0.001761461,0.001459344,0.007382453],"category_scores_gemma":[0.1192578,0.0007664202,0.0008355197,0.001363522,0.002309783,0.006726849,0.003049275,0.002231177,0.001246842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001167034,"about_ca_system_score_gemma":0.001526636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00173975,"about_ca_topic_score_gemma":0.002301032,"domain_scores_codex":[0.9949732,0.002048921,0.0003364262,0.0009635666,0.001521731,0.0001562055],"domain_scores_gemma":[0.9512211,0.03018906,0.007753095,0.007161318,0.002570461,0.001104924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001820428,0.001169715,0.0808825,0.001522039,0.0008001406,0.0002452463,0.004621475,0.06126162,0.02726362,0.316795,0.02124546,0.4823727],"study_design_scores_gemma":[0.0001924106,0.00080649,0.06616507,0.0002955321,0.000279299,0.0006245863,0.0006885615,0.3575203,0.02350248,0.5231928,0.02639181,0.0003407099],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04863726,0.0002248937,0.9345481,0.0005478478,0.0000601774,0.0004508135,0.001897868,0.003057185,0.010576],"genre_scores_gemma":[0.6348497,0.0002661499,0.3569654,0.0003115457,0.00004744155,0.001744885,0.002374981,0.0006799801,0.002760077],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01236776,"threshold_uncertainty_score":0.06540781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05422884318763529,"score_gpt":0.2209271620137919,"score_spread":0.1666983188261566,"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."}}