{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001016188,0.0004812727,0.0003177877,0.0001777351,0.0001498677,0.0005182153,0.0008150747,0.0005710446,0.00468927],"category_scores_gemma":[0.000351693,0.0002055267,0.0005196002,0.000264258,0.0001173243,0.0007427266,0.0002071492,0.0003169559,0.001165661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002954792,"about_ca_system_score_gemma":0.0002906797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003000004,"about_ca_topic_score_gemma":0.003312917,"domain_scores_codex":[0.9999439,0.000007466215,0.000002041012,0.00001040442,0.00002870167,0.000007510779],"domain_scores_gemma":[0.9999069,0.00002566717,0.00001031219,0.00002301306,0.00002917352,0.000004851415],"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":[0.0000398354,0.00004571308,0.0006757232,0.0001148752,0.00003187902,0.0001153221,0.00004227196,0.925364,0.03435971,0.007839834,0.003319854,0.02805096],"study_design_scores_gemma":[0.000002391794,0.00002096196,0.0002394396,0.0000032378,0.000007586345,0.00002127852,0.000004487437,0.9939883,0.002410908,0.0008841202,0.002413915,0.000003369047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1153552,0.0008107449,0.8485252,0.0003312988,0.0001361306,0.00009187702,0.001175077,0.003861965,0.02971262],"genre_scores_gemma":[0.9131432,0.000621223,0.07559004,0.00005532506,0.00004025609,0.0000905351,0.0005659,0.0004808597,0.009412671],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00468927,"threshold_uncertainty_score":0.01568717,"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."}}