{"id":"W4416957045","doi":"10.1145/3774399.3774406","title":"Semantic, Orthographic, and Morphological Biases in Humans' Wordle Gameplay","year":2025,"lang":"en","type":"article","venue":"AI Matters","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"IBM (Canada); University of Toronto","funders":"","keywords":"Outcome (game theory); Game theory; Key (lock); Natural (archaeology)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001652424,0.0001096663,0.0001651501,0.000208753,0.00005373737,0.00002981731,0.00008980164,0.00006511737,0.0009583964],"category_scores_gemma":[0.00001854862,0.0000954867,0.000036137,0.0002298463,0.00009176214,0.00002712697,0.00005762752,0.0002014614,0.0001240045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009788176,"about_ca_system_score_gemma":0.000009634065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001030081,"about_ca_topic_score_gemma":0.00006718263,"domain_scores_codex":[0.999141,0.00006567209,0.0001718197,0.0003133201,0.00005919246,0.0002489849],"domain_scores_gemma":[0.999663,0.000120982,0.00002679589,0.0001436551,0.000008233134,0.00003734975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007499965,0.0001638082,0.8452346,0.00002278255,0.00005744731,0.0002892128,0.001098572,0.000009469892,0.0007864819,0.00670188,0.1409182,0.00464252],"study_design_scores_gemma":[0.0004519472,0.00003580889,0.9221951,0.00009414797,0.000008240459,0.00001123272,0.0002465818,0.000005988345,0.00001889077,0.00023676,0.07657994,0.0001153506],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9639113,0.0002934985,0.00005234038,0.03192125,0.000236355,0.0001081459,0.000001967803,0.00005905549,0.003416118],"genre_scores_gemma":[0.9487298,0.000024348,0.00009932129,0.04913354,0.0000170597,0.00001653174,0.000006384682,0.000007542263,0.00196554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07696047,"threshold_uncertainty_score":0.9999549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685972585107929,"score_gpt":0.3062418043302255,"score_spread":0.2893820784791462,"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."}}