{"id":"W7070556725","doi":"","title":"Optimization and visualization of rapid prototyping process parameters.","year":2004,"lang":"en","type":"dissertation","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Doping in Sports","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visualization; Process (computing); Virtual prototyping; Rapid prototyping; Function (biology); Selection (genetic algorithm)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009440845,0.0002585361,0.0005038712,0.0005056213,0.0007450195,0.00005069744,0.0004781095,0.0007014747,0.0004011803],"category_scores_gemma":[0.0003261002,0.0003622987,0.0001477195,0.0007844059,0.0003991704,0.0009889964,0.00005364854,0.0003184302,0.000006539731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002494942,"about_ca_system_score_gemma":0.0007028052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007046753,"about_ca_topic_score_gemma":0.001848568,"domain_scores_codex":[0.9977314,0.0002288635,0.0003375359,0.0005183386,0.0008564474,0.0003274526],"domain_scores_gemma":[0.9978712,0.00006926111,0.001000484,0.0002616933,0.0006405768,0.0001567425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.003736167,0.001402179,0.3098218,0.01235559,0.001079263,0.0001021068,0.605985,0.02012628,0.001999157,0.01646216,0.0001875473,0.0267428],"study_design_scores_gemma":[0.01141964,0.001794716,0.6180974,0.01844862,0.002872909,0.00002007674,0.297495,0.001282902,0.02038199,0.01324487,0.008936036,0.006005822],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882872,0.0004195266,0.0002640004,0.00009372638,0.0003101937,0.001382475,0.00002163265,0.00009464831,0.009126602],"genre_scores_gemma":[0.9921269,0.0006456426,0.003073755,0.00001863752,0.00005291108,0.000003836819,0.0005831519,0.00005219019,0.003442933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.30849,"threshold_uncertainty_score":0.9998829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02243062891273795,"score_gpt":0.2940014771871742,"score_spread":0.2715708482744363,"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."}}