{"id":"W2235120461","doi":"10.37236/5417","title":"Guaranteed Scoring Games","year":2016,"lang":"en","type":"preprint","venue":"The Electronic Journal of Combinatorics","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Fundação para a Ciência e a Tecnologia; Ministério da Ciência, Tecnologia e Ensino Superior; Killam Trusts","keywords":"Monoid; Congruence (geometry); Quotient; Mathematics; Combinatorial game theory; Class (philosophy); Property (philosophy); Combinatorics; Order (exchange); Characterization (materials science); Inverse; Discrete mathematics; Computer science; Mathematical economics; Game theory; Sequential game; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.002465404,0.000333921,0.0005498096,0.0002476664,0.0001640417,0.0002841548,0.005784681,0.0002037017,0.000009230655],"category_scores_gemma":[0.000317508,0.0001989965,0.0003892738,0.0003566404,0.0001454258,0.0003176434,0.001366055,0.002269823,0.00004056543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007055004,"about_ca_system_score_gemma":0.001720971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008536292,"about_ca_topic_score_gemma":0.00000277012,"domain_scores_codex":[0.996682,0.0002828802,0.0009353127,0.0003126569,0.0008997871,0.0008873604],"domain_scores_gemma":[0.9962004,0.0005209719,0.001400215,0.001188592,0.0005897086,0.0001000869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001850358,0.00006118261,0.0001123697,0.00001709256,0.0001384142,0.00002203282,0.0006663167,0.0002162927,0.00021169,0.9888508,0.0006311564,0.009054097],"study_design_scores_gemma":[0.0001371933,0.0002565157,0.00003735372,0.0002702416,0.0000420681,0.0002023063,0.00004920917,0.001337482,0.009584923,0.9826143,0.00522421,0.000244231],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04462467,0.01246159,0.9294645,0.005141897,0.006178419,0.0002349108,0.000001026127,0.00008617529,0.001806864],"genre_scores_gemma":[0.9970407,0.001791962,0.0001406918,0.0001369265,0.0004734551,0.000005425733,1.182541e-7,0.00002800219,0.00038267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9524161,"threshold_uncertainty_score":0.9995945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01957512493069027,"score_gpt":0.2739163162272167,"score_spread":0.2543411912965264,"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."}}