{"id":"W1608664608","doi":"10.1109/icassp.1988.196770","title":"Long correlation random field image models","year":2003,"lang":"en","type":"article","venue":"","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Random field; Markov random field; Conditional random field; Generalization; Computer science; Field (mathematics); Artificial intelligence; Markov chain; Image (mathematics); Algorithm; Machine learning; Mathematics; Statistics; Image segmentation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001892848,0.0009335957,0.001215645,0.001433372,0.0004450864,0.001923168,0.003026567,0.002488663,0.009075611],"category_scores_gemma":[0.004856846,0.0005171091,0.00119739,0.001880534,0.001145097,0.003236488,0.0009848792,0.001708429,0.004595329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152203,"about_ca_system_score_gemma":0.000903291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007057992,"about_ca_topic_score_gemma":0.005181689,"domain_scores_codex":[0.9990915,0.0002845826,0.00003809747,0.0002273023,0.0002206508,0.0001378327],"domain_scores_gemma":[0.9980804,0.0008754443,0.0003303137,0.0002564496,0.0003808237,0.00007662734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006190321,0.00006156092,0.001096634,0.0001329395,0.00006505578,0.0002092353,0.00009208382,0.5032533,0.002114715,0.4412003,0.009833622,0.04187858],"study_design_scores_gemma":[0.00001040755,0.00001731322,0.0002414919,0.00001459713,0.00001319469,0.0001030188,0.00001066312,0.9153938,0.0003160792,0.07915834,0.00469822,0.00002290626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007832692,0.001099086,0.980076,0.0008229295,0.0001006187,0.00008413508,0.001179153,0.0009240452,0.007881295],"genre_scores_gemma":[0.5332365,0.004693665,0.3847477,0.001121071,0.0006089678,0.0008775951,0.0044336,0.0008223626,0.06945853],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009075611,"threshold_uncertainty_score":0.03036094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009448337099311742,"score_gpt":0.2130452320412291,"score_spread":0.2035968949419173,"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."}}