{"id":"W2098972463","doi":"10.1109/igarss.1989.577831","title":"Digital Enhancement Of Star-1 Sar Imagery For Linear Feature Extraction","year":2005,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Feature extraction; Computer science; Extraction (chemistry); Star (game theory); Artificial intelligence; Computer vision; Synthetic aperture radar; Pattern recognition (psychology); Remote sensing; Geology; Physics; Chemistry; Astrophysics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002097365,0.000319343,0.0002078456,0.0005302017,0.0001110589,0.0004524771,0.0001723865,0.0002963064,0.004032446],"category_scores_gemma":[0.0004221797,0.0001967594,0.0002693163,0.0004738469,0.0001444526,0.000382509,0.0002434231,0.0003011063,0.001254164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001175299,"about_ca_system_score_gemma":0.0002429063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003529387,"about_ca_topic_score_gemma":0.0008751408,"domain_scores_codex":[0.9999335,0.00001007047,0.000003593834,0.00001065517,0.00003134952,0.00001086225],"domain_scores_gemma":[0.9998461,0.00004676553,0.00001265106,0.00002444854,0.00006048823,0.000009609736],"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":[0.0003662465,0.00006049753,0.001219603,0.000252669,0.00002856502,0.0001368924,0.0001065348,0.008277204,0.7334886,0.00193489,0.002336489,0.2517917],"study_design_scores_gemma":[0.00003601997,0.0003569005,0.01920964,0.00004096099,0.0001179961,0.001786429,0.0001115524,0.1806933,0.7662184,0.001771071,0.02962368,0.00003406467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2631651,0.00112284,0.7169247,0.0005441543,0.0001325669,0.000117522,0.0006712468,0.001838574,0.01548331],"genre_scores_gemma":[0.4450935,0.001486893,0.5363247,0.000192045,0.00007416576,0.00006313207,0.001116126,0.0003422661,0.01530711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004032446,"threshold_uncertainty_score":0.01348984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01604662412189928,"score_gpt":0.3125469251069838,"score_spread":0.2965003009850845,"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."}}