{"id":"W2054260492","doi":"10.1109/icif.2007.4408172","title":"Automated learning multi-criteria classifiers for FLIR ship imagery classification","year":2007,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Artificial intelligence; Computer science; Random subspace method; Naive Bayes classifier; Machine learning; Statistical classification; Pattern recognition (psychology); Data mining; Support vector machine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007815485,0.0002519758,0.0002190007,0.0002650653,0.0001595976,0.0001441412,0.0001557985,0.0002186439,0.00003490466],"category_scores_gemma":[0.0003794242,0.0002674368,0.0001037156,0.0003363329,0.00007689244,0.0003270214,0.00001563211,0.0002600133,0.0001483433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002746383,"about_ca_system_score_gemma":0.00002528345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006714262,"about_ca_topic_score_gemma":0.00001365044,"domain_scores_codex":[0.9983967,0.00004163955,0.0005063502,0.0003502696,0.0001787485,0.0005263041],"domain_scores_gemma":[0.9989647,0.0002677757,0.00008746315,0.0003544498,0.0001831003,0.0001425419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003237516,0.00003618273,0.0004436299,0.0001111053,0.00003000597,0.000004575718,0.0002528983,0.002114031,0.9580057,0.0002006238,0.01180383,0.02696503],"study_design_scores_gemma":[0.000510114,0.000021376,0.03731102,0.00002543386,0.00001974573,0.00000918573,0.0003828351,0.9098151,0.0416531,0.00002178966,0.00992286,0.0003074403],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06616031,0.00005064487,0.9169967,0.0002063694,0.0008566988,0.0005089964,0.000004306424,0.006241448,0.008974549],"genre_scores_gemma":[0.8870371,0.00001234603,0.1107771,0.00006745279,0.0001628826,0.00001498516,0.0001235258,0.0001079383,0.0016966],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9163526,"threshold_uncertainty_score":0.9999778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05527929841485289,"score_gpt":0.3142312569847577,"score_spread":0.2589519585699048,"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."}}