{"id":"W4231505188","doi":"10.1093/jicru_ndp027","title":"Glossary of Imaging Terms","year":2009,"lang":"en","type":"article","venue":"Journal of the ICRU","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Computer science; Natural language processing; Linguistics; Philosophy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008112477,0.002244953,0.001746558,0.01081167,0.00177495,0.003874226,0.002009061,0.001964665,0.3764405],"category_scores_gemma":[0.006418921,0.0006587536,0.0007180654,0.0113532,0.0008305875,0.004430796,0.002211304,0.002416257,0.3499953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001275682,"about_ca_system_score_gemma":0.00189479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004399317,"about_ca_topic_score_gemma":0.005162916,"domain_scores_codex":[0.9992551,0.0001220459,0.0001446243,0.0001129073,0.000285843,0.00007936634],"domain_scores_gemma":[0.9975261,0.0009048,0.0002812751,0.0002948564,0.0008378756,0.0001551569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007243703,0.00002826645,0.0001008591,0.001439472,0.000008034416,0.0001599993,0.00007331843,0.000124663,0.001223863,0.01422255,0.9293741,0.05317242],"study_design_scores_gemma":[0.000008609937,0.000009498067,0.0001298919,0.0004058379,0.000009321147,0.0001880188,0.00002837953,0.00006690712,0.0002214461,0.00285427,0.9960657,0.00001212453],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001292015,0.04915641,0.0215061,0.00438325,0.01276558,0.001037057,0.1616486,0.003102371,0.7451085],"genre_scores_gemma":[0.01651726,0.0865469,0.04825101,0.009249884,0.009619192,0.002848674,0.2773195,0.007821534,0.5418261],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3764405,"threshold_uncertainty_score":0.8894319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003211265359745297,"score_gpt":0.1945931041391566,"score_spread":0.1913818387794113,"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."}}