{"id":"W2072910132","doi":"10.1149/05201.0765ecst","title":"Yellowing Mechanism and Solution for Chip Card Module","year":2013,"lang":"en","type":"article","venue":"ECS Transactions","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Infineon Technologies (Canada)","funders":"","keywords":"Curing (chemistry); Fourier transform infrared spectroscopy; Nitrogen; Mold; Chip; Chemistry; Materials science; Chemical engineering; Polymer chemistry; Composite material; Computer science; Engineering; Organic chemistry; Telecommunications","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":[0.00007502668,0.00007813812,0.00009514042,0.00006613669,0.0001653252,0.00004211671,0.0000214928,0.0001008533,0.00004670269],"category_scores_gemma":[0.000003377043,0.00007958421,0.00006297199,0.00007397307,0.000006769586,0.0001780549,8.558959e-7,0.00009183298,0.00003362925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000323949,"about_ca_system_score_gemma":0.000004453015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001068346,"about_ca_topic_score_gemma":0.00001620579,"domain_scores_codex":[0.9995735,0.000009196364,0.0001231703,0.00009742499,0.00005770494,0.0001389864],"domain_scores_gemma":[0.9998108,0.00002505441,0.000009757737,0.00007825086,0.00002564927,0.00005050574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002346268,0.00005705401,0.00001903907,0.0002652573,0.0002930277,0.000001142845,0.001594123,0.05912761,0.746121,0.001927516,0.004192371,0.1863783],"study_design_scores_gemma":[0.001446491,0.0001609159,0.0003997742,0.00006208859,0.00009433422,0.00003119542,0.0003515873,0.8368055,0.1323808,0.003800737,0.02398549,0.000481104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.150114,0.00005071659,0.847287,0.00004231813,0.001077765,0.0003899935,0.00001045794,0.0002285173,0.0007991657],"genre_scores_gemma":[0.9981098,0.00001180722,0.001142505,0.000006822292,0.0001425184,0.0001593779,0.000002102214,0.00002020523,0.0004048264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8479958,"threshold_uncertainty_score":0.324535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01591771101376241,"score_gpt":0.2040728065613757,"score_spread":0.1881550955476133,"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."}}