{"id":"W4392172381","doi":"10.1007/978-3-031-54968-7_4","title":"Solving NoGo on Small Rectangular Boards","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science","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":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001164344,0.0007344984,0.0005970005,0.001272432,0.0002895996,0.001338527,0.005134325,0.00046273,0.00004892642],"category_scores_gemma":[0.0002172014,0.0006616475,0.0002527245,0.0009032122,0.0008349043,0.0004373868,0.002075593,0.00155018,0.0008490491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005850742,"about_ca_system_score_gemma":0.0005754214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004373063,"about_ca_topic_score_gemma":0.0001402452,"domain_scores_codex":[0.9946048,0.00003372866,0.0006941075,0.002421989,0.001289133,0.0009563011],"domain_scores_gemma":[0.9964156,0.0007811773,0.000223225,0.002101543,0.0002497282,0.0002287717],"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":[0.000005652991,0.00002641856,0.000009610495,0.00005160134,0.00001770229,0.0004811123,0.00152421,0.02420354,0.0002313298,0.1882064,0.0001437355,0.7850987],"study_design_scores_gemma":[0.00003859333,0.0002611204,0.000007420738,0.001033819,0.00001001815,0.0000625494,3.545764e-7,0.4563808,0.008485788,0.5248795,0.00803483,0.0008052157],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001018815,0.001218011,0.9633063,0.001645509,0.006061099,0.0003836567,0.000004496664,0.0004982835,0.02678073],"genre_scores_gemma":[0.1593992,0.0002086417,0.8200514,0.006963791,0.003467968,0.00004112946,0.000006775876,0.0002377909,0.009623342],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7842935,"threshold_uncertainty_score":0.9999289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03067347035679165,"score_gpt":0.2692230715275089,"score_spread":0.2385496011707172,"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."}}