{"id":"W4241128676","doi":"10.14322/publons.r1035621","title":"10.14322/publons.r1035621","year":2000,"lang":"en","type":"dataset","venue":"Time to knit","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Chain code; Code (set theory); Pixel; Computer science; Chain (unit); Artificial intelligence; Mathematics; Programming language; Statistics; Image (mathematics); Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001141321,0.005548036,0.002085098,0.003430233,0.001022016,0.003050978,0.004551401,0.003284038,0.1983512],"category_scores_gemma":[0.003342689,0.001354006,0.001581147,0.004594683,0.0008762272,0.001847663,0.003189043,0.001675206,0.50152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001649106,"about_ca_system_score_gemma":0.001645945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01694202,"about_ca_topic_score_gemma":0.03073341,"domain_scores_codex":[0.9985912,0.0001545952,0.0001141897,0.0005136883,0.0003188368,0.0003075223],"domain_scores_gemma":[0.998514,0.0001540019,0.0001311493,0.0005972104,0.0003496611,0.0002539054],"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":[0.00009589162,0.00005044799,0.0003633538,0.0004013007,0.00002308369,0.00002129205,0.00001498663,0.0002667711,0.0003339844,0.0001865117,0.9932052,0.005037087],"study_design_scores_gemma":[0.0003859704,0.0001133436,0.002807501,0.0002182834,0.00004557501,0.0001617313,0.00009173925,0.001862319,0.002210591,0.0009523157,0.9910908,0.00005990631],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005790615,0.0002448496,0.0003847856,0.0001192014,0.0001474474,0.00005490285,0.9903799,0.005079185,0.003010598],"genre_scores_gemma":[0.0005933105,0.00007322704,0.0003975359,0.00006096407,0.00001878892,0.00006885279,0.995678,0.0002231292,0.002886161],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8016489,"threshold_uncertainty_score":0.6635507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007120997148260065,"score_gpt":0.1737857165802449,"score_spread":0.1666647194319849,"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."}}