{"id":"W2079210397","doi":"10.1109/icinfa.2014.6932711","title":"Visual ore quality assessment by image analysis","year":2014,"lang":"en","type":"article","venue":"","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Artificial intelligence; Computer science; Grayscale; Computer vision; Image processing; Visual inspection; Pattern recognition (psychology); Image segmentation; Image quality; Quality (philosophy); Segmentation; Image (mathematics); Feature extraction","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":[0.0002641659,0.00008237515,0.0001509879,0.00006201377,0.0000416824,0.00006118572,0.00006175417,0.00003405519,0.0003608562],"category_scores_gemma":[0.00001276573,0.00006919423,0.00005903604,0.0002580079,0.00001012702,0.00008181764,0.00001258908,0.00008074832,0.0000305161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002634633,"about_ca_system_score_gemma":0.000003030254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006094241,"about_ca_topic_score_gemma":0.00002242641,"domain_scores_codex":[0.9994605,0.00002301277,0.0001461326,0.0001114006,0.0001162846,0.0001426432],"domain_scores_gemma":[0.9997741,0.00003293381,0.00001530362,0.0001063747,0.00001663479,0.00005468381],"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":[0.00001072652,0.0003045458,0.1274212,0.0007782471,0.002597074,0.000004776095,0.0007016289,0.09955623,0.4655117,0.009047436,0.1812821,0.1127843],"study_design_scores_gemma":[0.0002287588,0.00002156568,0.02245149,0.000006382587,0.0001469923,3.882892e-7,0.00009159801,0.9632212,0.006110986,0.0001898488,0.007192768,0.0003380244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5852627,0.00002182476,0.3337509,0.00005590776,0.0000530171,0.00001846369,0.000003254366,0.0003142878,0.08051968],"genre_scores_gemma":[0.9943525,0.000002188176,0.003942879,0.00004794377,0.00004513301,0.000002862883,0.00002957831,0.000009807287,0.001567065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.863665,"threshold_uncertainty_score":0.3951122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118513505366508,"score_gpt":0.3185945860670284,"score_spread":0.3067432355303776,"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."}}