{"id":"W2911411839","doi":"","title":"Interview with Jeff Hancock","year":2018,"lang":"en","type":"article","venue":"Intersect: The Stanford Journal of Science, Technology and Society","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Deception; Officer; Psychology; Interpersonal communication; Media studies; Sociology; Library science; Political science; Social psychology; Computer science; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.003428614,0.00009053398,0.0001587363,0.0003165459,0.001556316,0.0001522379,0.0008167443,0.0001064518,0.0001275512],"category_scores_gemma":[0.0002819413,0.00004929483,0.00008001731,0.002089821,0.01289492,0.0008808739,0.0001100421,0.0003581064,0.000009150192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001022031,"about_ca_system_score_gemma":0.0004694305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000103225,"about_ca_topic_score_gemma":0.00007761375,"domain_scores_codex":[0.9987586,0.00003888689,0.000287488,0.00009697631,0.000476499,0.0003415089],"domain_scores_gemma":[0.9987176,0.00005238438,0.0003248247,0.0001543312,0.0006293972,0.0001214351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001135409,0.00007956354,0.001111219,0.00002811574,0.000182153,0.000007961741,0.4963281,0.000002587129,0.001428665,0.30142,0.03850381,0.1607942],"study_design_scores_gemma":[0.0006369407,0.001368556,0.0009744039,0.0002613209,0.00003685087,0.0002477893,0.6392776,0.0001379512,0.002755776,0.009699306,0.3443989,0.0002045993],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9079136,0.0002676087,0.006216886,0.01847189,0.0007481638,0.0001751026,0.000002089349,0.00006254793,0.06614215],"genre_scores_gemma":[0.9962669,0.0003706282,0.001050798,0.001522387,0.0001170267,4.776238e-7,4.111757e-8,0.000003373593,0.0006683466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.305895,"threshold_uncertainty_score":0.9997435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01664522024365045,"score_gpt":0.3031702022662573,"score_spread":0.2865249820226069,"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."}}