{"id":"W2965430906","doi":"10.5465/ambpp.2019.13404abstract","title":"The Crowd Classification Problem","year":2019,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Voting; Computer science; Group decision-making; Contingency; Framing (construction); Framing effect; Social choice theory; Point (geometry); Artificial intelligence; Machine learning; Social psychology; Psychology; Mathematics; Mathematical economics; Persuasion; Politics","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":[],"consensus_categories":[],"category_scores_codex":[0.001192361,0.00005466395,0.00006136063,0.00005862816,0.0002851069,0.0001117057,0.0003596014,0.00005930519,0.000115791],"category_scores_gemma":[0.00003825264,0.00004021811,0.00002862159,0.0002741752,0.0001004126,0.0006497129,0.00004922693,0.00009157092,0.0002303833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003845797,"about_ca_system_score_gemma":0.00001074569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008473991,"about_ca_topic_score_gemma":0.00000110005,"domain_scores_codex":[0.9990435,0.000007895448,0.0002078651,0.00009517636,0.0004411532,0.0002044172],"domain_scores_gemma":[0.9996548,0.0000268896,0.0001891367,0.00003461453,0.00004546596,0.00004913262],"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":[0.000007167294,0.000007535758,0.000526319,0.00005312812,0.00001285855,6.132038e-9,0.005734211,5.765329e-7,0.00008739694,0.9254268,0.0376782,0.03046579],"study_design_scores_gemma":[0.0001708842,0.00001277605,0.02702898,0.00003026128,0.000009251636,8.715912e-8,0.02281792,0.00007657581,0.0001752853,0.006878495,0.9427306,0.00006887177],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.114164,0.00002970703,0.00001403448,0.01656304,0.00005069044,0.0006073893,2.780107e-7,0.00005680184,0.8685141],"genre_scores_gemma":[0.9620985,0.0005882547,0.0002538609,0.0006219047,0.00004342376,0.0000067822,4.122455e-7,0.000004431321,0.03638242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9185483,"threshold_uncertainty_score":0.2961188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03120601969565532,"score_gpt":0.3165403632839792,"score_spread":0.2853343435883239,"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."}}