{"id":"W2006655378","doi":"10.1080/01969722.2012.732797","title":"QUANTIFYING NEARNESS IN VISUAL SPACES","year":2012,"lang":"en","type":"article","venue":"Cybernetics & Systems","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Measure (data warehouse); Similarity (geometry); Similarity measure; Computer science; Image (mathematics); Matching (statistics); Set (abstract data type); Artificial intelligence; Cybernetics; Earth mover's distance; Pattern recognition (psychology); Mathematics; Data mining; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005931024,0.0001136211,0.0001634138,0.0001085629,0.00005001279,0.0002659324,0.0004535519,0.00007957986,0.000003742967],"category_scores_gemma":[0.00003902322,0.0001011292,0.00003377514,0.0004403129,0.00003530592,0.000406931,0.0001199372,0.0001199579,0.0001404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000551791,"about_ca_system_score_gemma":0.00002892923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000131466,"about_ca_topic_score_gemma":0.000004385595,"domain_scores_codex":[0.9988136,0.0001127157,0.0002693143,0.0002013613,0.0002597624,0.0003432316],"domain_scores_gemma":[0.999342,0.00006900676,0.0001070855,0.0003239662,0.00006266262,0.00009524004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007324752,0.0004245437,0.1343378,0.000225587,0.00002014049,0.00001556461,0.004938295,0.00002653907,0.0184597,0.7958036,0.0009254414,0.04481543],"study_design_scores_gemma":[0.001295681,0.000316616,0.1915583,0.0008162251,0.00002905414,0.0002162629,0.002105308,0.330279,0.1448563,0.001145947,0.3250919,0.002289389],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1691655,0.006646556,0.8132322,0.0003551686,0.002041277,0.0005145654,0.00000127707,0.0006090346,0.007434385],"genre_scores_gemma":[0.9968018,0.00004487387,0.002308842,0.00002756013,0.0001392043,0.00002557007,0.000001242745,0.00001002443,0.0006408742],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8276364,"threshold_uncertainty_score":0.4123929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04681242619161964,"score_gpt":0.3129967717192166,"score_spread":0.266184345527597,"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."}}