{"id":"W3111979888","doi":"10.3390/min10121138","title":"Hyperspectral Characteristics of Oil Sand, Part 1: Prediction of Processability and Froth Quality from Measurements of Ore","year":2020,"lang":"en","type":"article","venue":"Minerals","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Alberta","funders":"University of Alberta","keywords":"Oil sands; Asphalt; Environmental science; Hyperspectral imaging; Froth flotation; Extraction (chemistry); Geology; Mining engineering; Materials science; Metallurgy; Chemistry; Composite material","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.000143912,0.0003627171,0.0001484861,0.0004519232,0.0001792675,0.0003434966,0.0002330685,0.0002977372,0.0004582214],"category_scores_gemma":[0.0004800597,0.0001335111,0.0002167874,0.0003168916,0.0001885087,0.000307117,0.0001465019,0.0002593444,0.0002038042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004903682,"about_ca_system_score_gemma":0.0004456475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05080294,"about_ca_topic_score_gemma":0.06919613,"domain_scores_codex":[0.9999238,0.000005718773,0.000002334622,0.00001789591,0.00003993739,0.00001020832],"domain_scores_gemma":[0.999894,0.00003257213,0.00001924957,0.00001049401,0.00003478739,0.000008888207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005919245,0.0004362064,0.1527869,0.0001482404,0.0001042067,0.0002025942,0.0001845794,0.3060296,0.4054927,0.0005366362,0.001258365,0.132228],"study_design_scores_gemma":[0.00001487305,0.00007021402,0.1517768,0.000005891717,0.00002339058,0.00006253952,0.00007107652,0.7710283,0.0759015,0.0002943008,0.0007217915,0.00002943342],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965351,0.00006923616,0.03175183,0.00005068586,0.000005122822,0.00003387773,0.0007084859,0.0003463473,0.001683387],"genre_scores_gemma":[0.9869937,0.00006556435,0.01134865,0.000009836543,0.000002463001,0.00001236384,0.0007125103,0.00002183454,0.0008330022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05080294,"threshold_uncertainty_score":0.1010145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08094919202166512,"score_gpt":0.2588010626079685,"score_spread":0.1778518705863034,"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."}}