{"id":"W7101255619","doi":"","title":"www.pum.umontreal.ca/revues/surfaces","year":2015,"lang":"en","type":"article","venue":"","topic":"Cultural Insights and Digital Impacts","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Work (physics); Product (mathematics); Process (computing); Set (abstract data type)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001043578,0.0008745352,0.0005943697,0.002218578,0.001783146,0.007175051,0.001749018,0.002339405,0.7823533],"category_scores_gemma":[0.002573624,0.0007171076,0.0005138015,0.002985752,0.0009795158,0.003473142,0.002850971,0.001012047,0.5165149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002754072,"about_ca_system_score_gemma":0.001927737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03035998,"about_ca_topic_score_gemma":0.05675346,"domain_scores_codex":[0.9992306,0.00006150306,0.00003129279,0.00008221397,0.0005108103,0.00008355773],"domain_scores_gemma":[0.9988326,0.0001970965,0.0000497209,0.0003011473,0.00035565,0.0002637173],"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":[0.00003833576,0.00002173596,0.000253023,0.0004366054,0.000005164603,0.00007530111,0.0001758965,0.0002778774,0.0007225984,0.03436604,0.7875116,0.1761157],"study_design_scores_gemma":[0.000001947315,0.000001684565,0.00008060299,0.00005963703,8.844203e-7,0.00003011603,0.0000462422,0.00005816893,0.0001467721,0.001032987,0.9985383,0.000002764801],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007955753,0.006137622,0.004334397,0.003664022,0.001233192,0.00007365489,0.005072177,0.005711715,0.9729776],"genre_scores_gemma":[0.01065446,0.008053322,0.005396551,0.0007857039,0.0004370833,0.00008243319,0.003344041,0.004957322,0.9662892],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2176467,"threshold_uncertainty_score":0.3104466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2899442803525145,"score_gpt":0.3024118155638112,"score_spread":0.01246753521129668,"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."}}