{"id":"W1929760380","doi":"10.1109/ictta.2004.1307578","title":"Data reduction in machine vision and remote sensing applications","year":2004,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Artificial intelligence; Machine vision; Artificial neural network; Computer vision; Reduction (mathematics); Artificial vision","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":[0.0009679773,0.0007099519,0.0011811,0.001305707,0.0004891929,0.001157004,0.001208598,0.0009686882,0.00313321],"category_scores_gemma":[0.00255172,0.0004095238,0.0008336548,0.003153089,0.0006480254,0.001184488,0.0008195255,0.001264193,0.002021157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004283336,"about_ca_system_score_gemma":0.0005958064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001976852,"about_ca_topic_score_gemma":0.001587548,"domain_scores_codex":[0.9989305,0.0002159997,0.0001060211,0.0001741752,0.0005251282,0.00004816692],"domain_scores_gemma":[0.9989843,0.0004895265,0.00005891876,0.0001331903,0.0003170015,0.00001699845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007584495,0.00006637343,0.0007653124,0.001302754,0.00009563728,0.0001297122,0.00008348866,0.02605354,0.01033383,0.02094148,0.007380072,0.932772],"study_design_scores_gemma":[0.00005202107,0.0002846101,0.006150174,0.0004676688,0.0001988067,0.0009710759,0.0002889504,0.5550039,0.05846686,0.1439687,0.2340189,0.0001283677],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008190747,0.03562742,0.9453383,0.001067916,0.0005827093,0.0001241225,0.000321038,0.0006966462,0.008051114],"genre_scores_gemma":[0.1355104,0.04937933,0.7981848,0.0008405034,0.001312222,0.0004630031,0.001531092,0.0002469817,0.01253162],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00313321,"threshold_uncertainty_score":0.0104816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02797899918917735,"score_gpt":0.3427990105464288,"score_spread":0.3148200113572514,"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."}}