{"id":"W4400773139","doi":"10.2139/ssrn.4894998","title":"Adversarial Coordination and Public Information Design: Additional Material","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Media Influence and Politics","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Adversarial system; Public information; Business; Knowledge management; Computer science; Political science; Public relations; Artificial intelligence","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":["research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002669954,0.0001620468,0.0001673518,0.0002696288,0.0004899248,0.000912365,0.0002631489,0.0003642325,0.001195478],"category_scores_gemma":[0.000658666,0.0001595143,0.00008101623,0.0001174793,0.0001818667,0.0006795924,0.0001622563,0.002384528,0.0001382601],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001533576,"about_ca_system_score_gemma":0.0155312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005239153,"about_ca_topic_score_gemma":0.000773354,"domain_scores_codex":[0.9971215,0.0002848502,0.0003566716,0.0001443984,0.000585868,0.00150675],"domain_scores_gemma":[0.9991034,0.0001379138,0.0002465133,0.00008582863,0.0002570597,0.000169337],"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":[0.00003125407,0.000012968,0.00002678936,0.00003517352,0.0001198681,0.00000206762,0.00281718,0.00002549726,0.000004752927,0.963098,0.01572831,0.01809809],"study_design_scores_gemma":[0.0001884119,0.00006416671,0.00002243815,0.00006429935,0.00005488101,0.00004196939,0.003952747,0.0001229085,0.000005610727,0.8644625,0.1308338,0.0001863329],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5553157,0.008781957,0.07226428,0.1549823,0.08869333,0.007133991,0.009561266,0.00159444,0.1016727],"genre_scores_gemma":[0.9847724,0.00440184,0.0004129588,0.0003397777,0.007975503,0.00006991726,0.0008611698,0.0000219153,0.00114445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4294567,"threshold_uncertainty_score":0.999917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997582328836119,"score_gpt":0.2849161473287635,"score_spread":0.2649403240404023,"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."}}