{"id":"W2744748126","doi":"10.1149/ma2009-01/24/991","title":"Feature Scale Modeling for Through-Silicon-Via Packaging Applications","year":2009,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mitel (Canada)","funders":"","keywords":"Feature (linguistics); Scale (ratio); Silicon; Computer science; Artificial intelligence; Materials science; Pattern recognition (psychology); Optoelectronics; Cartography; Geography","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":[0.0003299032,0.0001674838,0.0001902006,0.00006290463,0.0002311198,0.00008639345,0.00009487723,0.0002026772,0.000002353774],"category_scores_gemma":[0.00004219765,0.0001712778,0.00009696414,0.0001710755,0.000006508722,0.0001636274,0.000006640124,0.0002540727,0.00003595589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006280973,"about_ca_system_score_gemma":0.00001217899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002466582,"about_ca_topic_score_gemma":0.000005157725,"domain_scores_codex":[0.9990375,0.00001142526,0.0002759716,0.0002222092,0.0001447782,0.0003081206],"domain_scores_gemma":[0.9994961,0.00007145404,0.00006557686,0.0002224198,0.00007313402,0.00007132311],"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":[0.000007554984,0.00001400966,0.00001534903,0.00004116887,0.0000114572,7.381138e-7,0.0001956666,0.908166,0.08063201,0.00001132774,0.002377762,0.008526954],"study_design_scores_gemma":[0.000972688,0.00008909739,0.0003146855,0.000327361,0.00005207743,0.00003699421,0.000367479,0.7158892,0.2049195,0.002260848,0.07407837,0.0006917324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6478565,0.001025218,0.1889835,0.0006989055,0.001644171,0.001917849,0.00002818683,0.00211623,0.1557294],"genre_scores_gemma":[0.9945191,0.000007515336,0.004174902,0.00005177129,0.0009867911,0.00006824208,0.00001361985,0.00003401917,0.0001440054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3466626,"threshold_uncertainty_score":0.6984504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964809073467482,"score_gpt":0.254248093539989,"score_spread":0.2346000028053141,"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."}}