{"id":"W4408435874","doi":"10.1117/12.3053040","title":"Smart roller: normal and three-axis stress measurement sensor array for automated fiber placement","year":2025,"lang":"en","type":"article","venue":"","topic":"Semiconductor Lasers and Optical Devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stress (linguistics); Computer science","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":[0.0005518871,0.0007640378,0.0005492619,0.0007065036,0.0002817554,0.0006295296,0.001026321,0.0007686199,0.004627842],"category_scores_gemma":[0.0007536404,0.0004159418,0.0002294319,0.0003880792,0.0004710341,0.001212446,0.0006109588,0.0005686656,0.002050076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004056813,"about_ca_system_score_gemma":0.0004585633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004410866,"about_ca_topic_score_gemma":0.001539963,"domain_scores_codex":[0.9988022,0.0001068568,0.00004906877,0.0002555641,0.0007224245,0.00006395863],"domain_scores_gemma":[0.9991713,0.0001149605,0.0002014287,0.0001808853,0.0002457261,0.00008579387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002062579,0.00007829113,0.001266156,0.0001467851,0.00001273727,0.0001604311,0.00009094541,0.001158249,0.9083136,0.001420634,0.004174807,0.082971],"study_design_scores_gemma":[0.00005943807,0.000780222,0.006056182,0.00001840014,0.00002251948,0.0008596298,0.0000625606,0.03186188,0.9288901,0.000597136,0.03066183,0.0001300784],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2599023,0.001604079,0.7069076,0.0009098873,0.0009848234,0.0006777403,0.002231618,0.01221025,0.01457168],"genre_scores_gemma":[0.5151365,0.0004064007,0.4685436,0.0005004865,0.000171736,0.0002856106,0.0007189364,0.0002585371,0.01397812],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004627842,"threshold_uncertainty_score":0.01548171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01572109364420246,"score_gpt":0.2261206858338259,"score_spread":0.2103995921896234,"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."}}