{"id":"W2313045937","doi":"10.4271/2016-01-1522","title":"An Algorithm to Calculate Chest Deflection from 3D IR-TRACC","year":2016,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Medical Imaging and Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Deflection (physics); Algorithm; Physics; Optics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005091013,0.0008018579,0.0009626402,0.0002956689,0.0002767536,0.0001415041,0.0009835771,0.0007806037,0.001244243],"category_scores_gemma":[0.0005062315,0.0005914734,0.0004353702,0.0009709069,0.0004915377,0.0005996402,0.0001819928,0.0009759247,0.0006744975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004672996,"about_ca_system_score_gemma":0.0000480487,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002252695,"about_ca_topic_score_gemma":0.02685725,"domain_scores_codex":[0.9955435,0.000134617,0.001001749,0.001255823,0.0009642792,0.001100067],"domain_scores_gemma":[0.9967961,0.0003967227,0.00009753334,0.001567036,0.00009678179,0.001045873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003144609,0.0001631591,0.0001568431,0.00001581341,0.00007901715,0.00004670748,0.00002192488,0.00008985277,0.8428621,0.0002308793,0.00269423,0.1536081],"study_design_scores_gemma":[0.000685399,0.0005107139,0.9133388,0.0003400806,0.0001865218,0.00003913572,0.00003958079,0.000009523309,0.001367671,0.001324557,0.0810913,0.001066724],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9384394,0.0006957141,0.001539707,0.01003146,0.001204077,0.001242416,0.0003723835,0.0163446,0.03013019],"genre_scores_gemma":[0.9748782,0.0003278609,0.02186611,0.001599474,0.0004970544,0.0002121493,0.00006135985,0.0001849051,0.0003728755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.913182,"threshold_uncertainty_score":0.9996688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009185931688601807,"score_gpt":0.2468181015832617,"score_spread":0.2376321698946599,"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."}}