{"id":"W2100206033","doi":"","title":"Communication Can Destroy Common Learning","year":2008,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Common knowledge (logic); Computer science; Common cause and special cause; Artificial intelligence; Engineering; Operations management","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","open_science","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.003007767,0.000397627,0.000693646,0.0006073448,0.0005078831,0.0004707688,0.004959086,0.0004856314,0.00001218764],"category_scores_gemma":[0.0005423255,0.000470811,0.0002128376,0.0003258357,0.0005393834,0.0002122283,0.01008119,0.004453928,0.0000206271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001966787,"about_ca_system_score_gemma":0.0009332382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007431493,"about_ca_topic_score_gemma":0.00101273,"domain_scores_codex":[0.9947152,0.001583584,0.0008533731,0.001381241,0.0004679504,0.0009987042],"domain_scores_gemma":[0.9939452,0.001497222,0.0003170944,0.003732973,0.0002360756,0.0002713919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001628339,0.0002908196,0.01986276,0.000089151,0.00005148561,0.00005988732,0.002027503,0.161737,0.00001831083,0.001838223,0.00006299988,0.8139456],"study_design_scores_gemma":[0.0006415103,0.0002102357,0.03006428,0.0002313001,0.000004827962,0.00008780392,0.0002866001,0.9299628,0.0001246202,0.01908782,0.01835039,0.0009478455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.844741,0.000806641,0.003510751,0.004110667,0.001267023,0.002610574,0.00003249412,0.000829946,0.1420909],"genre_scores_gemma":[0.9462005,0.01201332,0.04057789,0.00008840619,0.0001480122,0.000228651,0.00008578366,0.0000585518,0.0005988643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8129978,"threshold_uncertainty_score":0.9997743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04690211289920117,"score_gpt":0.3206472114535167,"score_spread":0.2737450985543155,"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."}}