{"id":"W2398001269","doi":"10.2352/cic.2011.19.1.art00030","title":"Fast Colour Vesselness","year":2011,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial intelligence; Computer vision; Grayscale; Computer science; Image (mathematics); Pixel; Hessian matrix; Pattern recognition (psychology); Mathematics","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":[0.00009847249,0.0001044185,0.0002054002,0.00007185328,0.00008247438,0.00004138418,0.00006628477,0.00002034486,0.0002490972],"category_scores_gemma":[0.0000509656,0.00008576392,0.00004165482,0.0001154118,0.0001712602,0.0000907648,0.00003964477,0.0001154027,0.0000322524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001016227,"about_ca_system_score_gemma":0.00006094638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001045449,"about_ca_topic_score_gemma":0.000002269446,"domain_scores_codex":[0.9993684,0.00001945908,0.0001241573,0.0002155393,0.00009280723,0.0001796033],"domain_scores_gemma":[0.9995118,0.00001810266,0.00004056264,0.0001555176,0.0001467544,0.0001272744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000263569,0.0002668064,0.8331281,0.0002064391,0.0001292391,0.000358394,0.003894323,2.877186e-7,0.03012921,0.005659466,0.002838466,0.1231257],"study_design_scores_gemma":[0.002302353,0.0003501552,0.9267761,0.0005115703,0.0007504469,0.0007120935,0.004099544,0.02705612,0.02195699,0.002006201,0.01280744,0.0006710318],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9261804,0.0003374505,0.003592875,0.001331504,0.00009158625,0.0001024464,0.000002527645,0.00009648639,0.06826475],"genre_scores_gemma":[0.9964573,0.00006155931,0.0009630612,0.0004874268,0.00003470471,0.000008293027,0.000004132293,0.000008945436,0.001974571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1224547,"threshold_uncertainty_score":0.3497351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03855580938296822,"score_gpt":0.2652537808638498,"score_spread":0.2266979714808816,"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."}}