{"id":"W2095409339","doi":"10.1145/1855118.1855133","title":"The story of set disjointness","year":2010,"lang":"en","type":"article","venue":"ACM SIGACT News","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Citation; Library science; Computer science; Set (abstract data type); World Wide Web; Media studies; Operations research; Sociology; Engineering; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001442476,0.00008489689,0.0002180658,0.00004656234,0.0001683317,0.00003341041,0.0005321504,0.00007084302,0.0001552454],"category_scores_gemma":[0.001210265,0.00006841229,0.00009041687,0.00009300816,0.0001029837,0.00008653582,0.0000761037,0.0002950469,0.0004419363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001001052,"about_ca_system_score_gemma":0.00001157648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001332697,"about_ca_topic_score_gemma":0.0001230469,"domain_scores_codex":[0.9992473,0.00003956475,0.0003475672,0.0001655754,0.00002381056,0.0001762378],"domain_scores_gemma":[0.9982963,0.0005147078,0.0003133954,0.0008141925,0.00001707941,0.00004433826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003104681,0.00005324164,0.08672617,0.00004020804,0.00005920786,0.000001485393,0.001896132,0.000008534506,0.002909191,0.8947768,0.007160728,0.006337276],"study_design_scores_gemma":[0.0005323118,0.00008524207,0.06878293,0.00001884988,0.000007173437,0.000008782574,0.0008478172,0.00009630274,0.002587291,0.1558908,0.7708134,0.0003291373],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811453,0.0003221184,0.00008412789,0.0009881833,0.001577341,0.0001104539,0.00003548987,0.00002466176,0.01571237],"genre_scores_gemma":[0.9967306,0.00002124073,0.00007007421,0.00006131839,0.000183569,0.000008968446,0.000002790062,0.00001415848,0.002907332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7636526,"threshold_uncertainty_score":0.5680345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0365966246474522,"score_gpt":0.2410202351192273,"score_spread":0.2044236104717751,"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."}}