{"id":"W4243372871","doi":"10.1109/seams.2019.00009","title":"Artifact Program Committee","year":2019,"lang":"en","type":"article","venue":"","topic":"Engineering and Material Science Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Artifact (error); Computer science; Computer graphics (images); Computer vision; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008908146,0.00109866,0.0008984024,0.004902004,0.003033996,0.007392559,0.002714913,0.001939603,0.470902],"category_scores_gemma":[0.01496833,0.0005826431,0.001042429,0.003007934,0.0006257938,0.002432772,0.003865284,0.002175163,0.3824499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002517731,"about_ca_system_score_gemma":0.009119767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005141459,"about_ca_topic_score_gemma":0.01299837,"domain_scores_codex":[0.9930824,0.001055488,0.0003007354,0.0006338127,0.004263083,0.0006644904],"domain_scores_gemma":[0.9705074,0.00154639,0.00070228,0.004013641,0.01863216,0.004598048],"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":[0.00006810361,0.00009343417,0.000341335,0.000103397,0.000003949912,0.00003157847,0.00004551238,0.00007504912,0.0008837485,0.006108528,0.9201423,0.07210303],"study_design_scores_gemma":[0.000009579451,0.00002429302,0.000391461,0.000033599,0.000003362383,0.00002743688,0.00003930643,0.0001028397,0.0006084429,0.0009036692,0.9978516,0.000004411826],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.003404589,0.001716498,0.02486742,0.01536151,0.01039883,0.0022545,0.01857195,0.006527488,0.9168972],"genre_scores_gemma":[0.002763255,0.0005271002,0.004621597,0.001698615,0.0007465953,0.0005121091,0.008500368,0.001108589,0.9795218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.470902,"threshold_uncertainty_score":0.7546941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01794864354397797,"score_gpt":0.3018514097343328,"score_spread":0.2839027661903549,"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."}}