{"id":"W4247936228","doi":"10.14322/publons.r1037817","title":"10.14322/publons.r1037817","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":"Metrology; Sampling (signal processing); Computer science; Data mining; Statistics; Mathematics; Computer vision","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":[0.001156456,0.005380751,0.002102284,0.003443824,0.0009660504,0.002936991,0.004546185,0.003166271,0.2074226],"category_scores_gemma":[0.003333388,0.001298463,0.001548109,0.004642478,0.0008612465,0.001869031,0.003144504,0.001599908,0.5192246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001573517,"about_ca_system_score_gemma":0.001608248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0159681,"about_ca_topic_score_gemma":0.02951332,"domain_scores_codex":[0.9985698,0.0001633557,0.0001146332,0.000531616,0.0003195856,0.000300891],"domain_scores_gemma":[0.9985223,0.0001520733,0.000131506,0.0006022916,0.0003400057,0.0002517837],"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":[0.00009822565,0.0000486836,0.0003456277,0.0003930788,0.00002258977,0.00001942524,0.00001432446,0.000262659,0.000335109,0.0001867554,0.9928936,0.005379825],"study_design_scores_gemma":[0.0003678469,0.0001133311,0.002617795,0.000209561,0.00004418408,0.0001580403,0.00008667488,0.001890619,0.002157178,0.0009572791,0.9913397,0.00005792864],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0006069726,0.0002705353,0.0004418788,0.0001234245,0.0001485108,0.00005950482,0.9893823,0.005569499,0.00339739],"genre_scores_gemma":[0.0006180089,0.00007898521,0.0004382659,0.0000634937,0.00001965735,0.00007377109,0.9952544,0.0002515311,0.003201892],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7925774,"threshold_uncertainty_score":0.6938978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007231978702022455,"score_gpt":0.1747578648982472,"score_spread":0.1675258861962247,"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."}}