{"id":"W1965202763","doi":"10.1155/2013/876386","title":"New Brodatz-Based Image Databases for Grayscale Color and Multiband Texture Analysis","year":2013,"lang":"en","type":"article","venue":"ISRN Machine Vision","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grayscale; Texture (cosmology); Artificial intelligence; Computer science; Pattern recognition (psychology); Texture compression; Chromatic scale; Texture filtering; Image texture; Computer vision; Bidirectional texture function; Image processing; Image (mathematics); Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001749383,0.0001535735,0.0002085171,0.0002132971,0.0001538644,0.0002779347,0.000391483,0.00004853396,0.0000790311],"category_scores_gemma":[0.0000866314,0.0001143723,0.0001042774,0.0006451329,0.00004413819,0.0006780212,0.0001377768,0.00008466049,0.00002668609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001974752,"about_ca_system_score_gemma":0.00005034705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005362,"about_ca_topic_score_gemma":0.00009765963,"domain_scores_codex":[0.9989133,0.0000420351,0.0002122559,0.0004455166,0.0001903923,0.0001965339],"domain_scores_gemma":[0.9988639,0.0002160476,0.0001023114,0.0005477747,0.0001337119,0.0001362311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006694927,0.000300438,0.004972239,0.0001262838,0.0001291228,0.000005258918,0.0001496747,0.00001388178,0.2316884,0.004870854,0.03526261,0.7224143],"study_design_scores_gemma":[0.000933752,0.0002555338,0.02983324,0.00002822438,0.0001176334,0.000004720724,0.00000968141,0.8518124,0.09932246,0.001461301,0.01587275,0.0003483572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005555575,0.0001992388,0.9908768,0.002520839,0.00004067041,0.0004529476,0.00005294312,0.0002306753,0.0000702977],"genre_scores_gemma":[0.3987199,0.00003469947,0.5997308,0.0003491605,0.00004651908,0.00004352608,0.0001499317,0.00001247057,0.0009128904],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8517985,"threshold_uncertainty_score":0.4663968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01099123100074101,"score_gpt":0.2941408181144594,"score_spread":0.2831495871137184,"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."}}