{"id":"W1955224945","doi":"10.1109/cbmsys.1990.109380","title":"Analysis directional features in images using Gabor filters","year":2002,"lang":"en","type":"article","venue":"","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial intelligence; Orientation (vector space); Gabor filter; Computer vision; Computer science; Gabor wavelet; Pattern recognition (psychology); Gaussian; Image (mathematics); Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006045004,0.0000707079,0.0001815134,0.000300709,0.00002525406,0.00002064562,0.00002785372,0.00003493081,0.001409984],"category_scores_gemma":[0.00004678798,0.00005507272,0.0000904788,0.0005671871,0.00004436328,0.00005329235,0.0000103758,0.000128667,0.000008116976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005669572,"about_ca_system_score_gemma":0.000005340069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002588907,"about_ca_topic_score_gemma":0.00001839412,"domain_scores_codex":[0.9994598,0.00001384856,0.0001066435,0.0001519126,0.0001228922,0.0001449167],"domain_scores_gemma":[0.9997553,0.0000282429,0.00001369087,0.0001194025,0.00002888431,0.0000544999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006928248,0.0007286911,0.7844511,0.0000403333,0.0006138888,0.0001895467,0.0002013178,0.00009123534,0.1712055,0.0008798976,0.0360585,0.005470621],"study_design_scores_gemma":[0.001034828,0.0002150912,0.6876457,0.0001008506,0.001209177,0.0001260724,0.0001188811,0.0712022,0.2355642,0.0003787736,0.001961194,0.0004429384],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7176382,0.0009785926,0.02523898,0.007831518,0.00009960273,0.0002718518,0.000009885021,0.0007257835,0.2472056],"genre_scores_gemma":[0.9070856,0.00005016056,0.08521497,0.0005187883,0.0000450494,0.000003588588,0.000004165942,0.000007259068,0.007070424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2401352,"threshold_uncertainty_score":0.9995028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01968651403594042,"score_gpt":0.3252510375068073,"score_spread":0.3055645234708669,"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."}}