{"id":"W1492796169","doi":"10.1109/mias.2014.2345801","title":"There's an App for That A Mobile Application for the Optimization of Electrolytic Tinning Line","year":2015,"lang":"en","type":"article","venue":"IEEE Industry Applications Magazine","topic":"Electrical Contact Performance and Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Stantec (Canada)","funders":"","keywords":"Line (geometry); Allowance (engineering); Engineering; Process optimization; Mechanical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002657527,0.0001341233,0.0001753476,0.00008460849,0.0001007687,0.00002533845,0.0002576685,0.0001841513,0.000008773054],"category_scores_gemma":[0.00001417759,0.000108905,0.00006901559,0.000544708,0.00002662964,0.0001646532,0.000007028802,0.0002101394,0.000008305072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006221872,"about_ca_system_score_gemma":0.00004648264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005053687,"about_ca_topic_score_gemma":0.000005978277,"domain_scores_codex":[0.9992176,0.000008365541,0.0002650626,0.0001779419,0.0001193603,0.0002117272],"domain_scores_gemma":[0.999084,0.0001288449,0.0001032078,0.0003927702,0.0002151005,0.00007607464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002441266,0.0000682318,0.0001097459,0.00004421357,0.00005825928,2.024826e-8,0.00004220249,0.9481096,0.0167031,0.0002810265,0.001310848,0.03324834],"study_design_scores_gemma":[0.0004127508,0.0001456185,0.00003879972,0.00000615447,0.0001210538,0.000001308741,0.00005537826,0.9443679,0.0226176,0.0002541878,0.03184802,0.0001312477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01472569,0.0004033959,0.9824517,0.0001503871,0.00003393974,0.001670613,0.00003085979,0.0001690599,0.0003643334],"genre_scores_gemma":[0.984094,0.00005533639,0.00420566,0.00005533507,0.0003687058,0.01061343,0.0001597663,0.00004110823,0.000406646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.978246,"threshold_uncertainty_score":0.4441016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03065454655387822,"score_gpt":0.2827154786252698,"score_spread":0.2520609320713916,"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."}}