{"id":"W4292387298","doi":"10.1109/lgrs.2022.3200311","title":"Interactive Fracture Segmentation Based on Optimum Connectivity Between Superpixels","year":2022,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"CODE; Petrobras; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Segmentation; Computer science; Annotation; Image segmentation; Pixel; Artificial intelligence; Cut; Path (computing); Pattern recognition (psychology); Computer vision","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000703323,0.000905645,0.0008484769,0.002100417,0.0005414939,0.0009099143,0.001360174,0.0009661221,0.002195733],"category_scores_gemma":[0.002391671,0.0004741017,0.001192002,0.001322666,0.0004751726,0.001344678,0.00104558,0.0006111428,0.0008442316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004869405,"about_ca_system_score_gemma":0.0007205493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008019782,"about_ca_topic_score_gemma":0.02248335,"domain_scores_codex":[0.9992357,0.00008977425,0.00003646451,0.0003501976,0.0002000146,0.00008778928],"domain_scores_gemma":[0.9989505,0.0004743772,0.0001124513,0.0001945017,0.0002110007,0.00005719707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00104821,0.0002217578,0.01139086,0.0005103765,0.0002011758,0.0006728026,0.00106473,0.08739606,0.1891868,0.00339352,0.008918815,0.6959949],"study_design_scores_gemma":[0.00004985704,0.0001216692,0.009657458,0.00004408336,0.00008036476,0.0008285294,0.0002854787,0.9175496,0.05939658,0.005415796,0.006524693,0.00004590301],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1795092,0.0004480761,0.8038015,0.0001789605,0.00003897891,0.0002563219,0.001139776,0.01181737,0.002809733],"genre_scores_gemma":[0.2976257,0.000163185,0.6972535,0.00009212052,0.00001910933,0.0001304545,0.002522947,0.001104619,0.001088428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008019782,"threshold_uncertainty_score":0.01594621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007203131985307372,"score_gpt":0.2192404095919392,"score_spread":0.2120372776066319,"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."}}