{"id":"W2275049566","doi":"","title":"CounterIntelligence, Justina M. Barnicke Gallery, Toronto, 24 January to 16 March 2014","year":2014,"lang":"fr","type":"article","venue":"Érudit (Université de Montréal)","topic":"Art, Technology, and Culture","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Counterintelligence; Computer science; Computer security","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002954699,0.0004844255,0.0004836286,0.0001301946,0.001629914,0.0000936793,0.00081132,0.0004393459,0.009436615],"category_scores_gemma":[0.00003643971,0.0005209111,0.0002732676,0.00007479427,0.0005120221,0.0003917523,0.00060343,0.0004507922,0.003040909],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005808806,"about_ca_system_score_gemma":0.00004535225,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04771007,"about_ca_topic_score_gemma":0.7289228,"domain_scores_codex":[0.9975905,0.0001328789,0.0003090579,0.0006612737,0.0003407678,0.0009655263],"domain_scores_gemma":[0.9984018,0.00008844382,0.0001661956,0.0007181185,0.000223046,0.0004023639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001177315,0.000107468,0.00006260545,0.00008123505,0.0001206115,0.0001910135,0.004022282,0.00003870665,0.0000635326,0.2551349,0.7088165,0.03124345],"study_design_scores_gemma":[0.0004111553,0.0005338514,0.0001945907,0.0001478128,0.0002101306,0.0001945507,0.01795181,0.0003158596,0.00006739656,0.001593649,0.9777625,0.000616653],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0192518,0.1653441,0.002761543,0.1007408,0.004322979,0.0008787882,0.0005246884,0.0006017212,0.7055735],"genre_scores_gemma":[0.08456529,0.03326356,0.0004168852,0.001911303,0.001662141,0.00002034047,0.0000904964,0.00006657746,0.8780034],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6812128,"threshold_uncertainty_score":0.9997243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008336154272271938,"score_gpt":0.1782218043716647,"score_spread":0.1698856500993928,"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."}}