{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001223155,0.0001451936,0.0001648263,0.00005378692,0.00005611787,0.00005185648,0.00006368986,0.00006341164,0.0002552053],"category_scores_gemma":[0.00001806674,0.0001195957,0.00004259291,0.00007834782,0.00001772799,0.00006750531,0.0000180668,0.00005639324,0.00001609886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006111382,"about_ca_system_score_gemma":0.00001318533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003308196,"about_ca_topic_score_gemma":0.0002267274,"domain_scores_codex":[0.9992681,0.000006112481,0.0001847555,0.0001632181,0.0001427916,0.0002350526],"domain_scores_gemma":[0.9996666,0.00005422541,0.00001102057,0.0001336567,0.00006674957,0.00006774524],"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":[0.0008294852,0.0007342891,0.0399593,0.007153918,0.005347138,0.00002357109,0.001086865,0.1558465,0.4844723,0.005227323,0.2608466,0.0384727],"study_design_scores_gemma":[0.003745246,0.000166729,0.01134152,0.0003043195,0.0002030999,0.000002096813,0.0004558888,0.5817491,0.3127223,0.0001360753,0.08839213,0.0007815366],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.908051,0.001621243,0.01736883,0.000761636,0.001205009,0.001547616,0.0001050506,0.00233431,0.06700528],"genre_scores_gemma":[0.9890169,0.00003004822,0.008389226,0.0002070021,0.00006104269,0.0001080835,0.00001670926,0.0000281121,0.002142899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4259026,"threshold_uncertainty_score":0.4876971,"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."}}