{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001041604,0.0002758171,0.0002155927,0.000547027,0.0001893096,0.002145017,0.0002403237,0.0004550636,0.002133442],"category_scores_gemma":[0.01078464,0.0003320625,0.0001170878,0.0001711665,0.001515395,0.0008683433,0.0008489314,0.000380646,0.0003075524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002348625,"about_ca_system_score_gemma":0.0001844494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001867034,"about_ca_topic_score_gemma":0.002649685,"domain_scores_codex":[0.9989629,0.0003212866,0.00005675981,0.0002514157,0.0003134032,0.00009420441],"domain_scores_gemma":[0.9967709,0.001823895,0.0006277247,0.0003330183,0.0002679595,0.0001764231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00165649,0.0003009842,0.5288652,0.0002859571,0.0002584282,0.0008875192,0.02679138,0.009132237,0.3250039,0.01143823,0.001235841,0.09414396],"study_design_scores_gemma":[0.0000909159,0.0009155695,0.8933721,0.00008045336,0.00009796409,0.001880198,0.007395408,0.04009847,0.0366946,0.01514086,0.004047898,0.0001856877],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994579,0.00004257143,0.00233301,0.00003529753,0.000004380965,0.000007610874,0.00003310976,0.00001947676,0.002945588],"genre_scores_gemma":[0.9986019,0.00001719675,0.00089625,0.00001819956,8.362724e-7,0.000006672748,0.00002240263,0.000008740075,0.0004278084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002145017,"threshold_uncertainty_score":0.00713706,"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."}}