{"id":"W3191807516","doi":"10.3390/min11080859","title":"ECORE: A New Fast Automated Quantitative Mineral and Elemental Core Scanner","year":2021,"lang":"en","type":"article","venue":"Minerals","topic":"Laser-induced spectroscopy and plasma","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Mitacs","keywords":"Hyperspectral imaging; Scanner; Elemental analysis; Chemical imaging; Laser-induced breakdown spectroscopy; Scanning electron microscope; Spectroscopy; Remote sensing; Mineralogy; Resolution (logic); Materials science; Optics; Geology; Chemistry; Computer science; Physics; Laser; Artificial intelligence","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":[0.00004858265,0.0001858757,0.000213414,0.00005142192,0.0000511319,0.00006413004,0.00006288213,0.00007541104,0.0006750249],"category_scores_gemma":[0.00002992031,0.0001783288,0.00004408418,0.0001977159,0.00002323328,0.0001437177,0.00003052171,0.0001256213,0.0001024261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004177867,"about_ca_system_score_gemma":0.00004113224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009023681,"about_ca_topic_score_gemma":0.0006518132,"domain_scores_codex":[0.9991771,0.00001878101,0.0001943515,0.0002079928,0.0001095996,0.0002921547],"domain_scores_gemma":[0.9996154,0.00005250179,0.00002108015,0.000138041,0.00002939275,0.0001436281],"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":[0.00001116202,0.00002115778,0.0004512409,0.00003179903,0.00007328519,0.0000961282,0.0004773057,0.001551099,0.8539308,0.001191666,0.14184,0.000324371],"study_design_scores_gemma":[0.002519908,0.0002482483,0.00415622,0.000139523,0.00008703638,0.0002277087,0.0006634574,0.281854,0.670293,0.0005943456,0.03824991,0.0009667066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902366,0.0003729769,0.00009842778,0.000238724,0.0003407543,0.00009026565,0.00008091034,0.0004654788,0.008075876],"genre_scores_gemma":[0.9829193,0.00005162507,0.007564463,0.0001895223,0.000168771,0.000009456356,0.0001753398,0.0000386666,0.008882834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2803029,"threshold_uncertainty_score":0.7391049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02253587226811899,"score_gpt":0.2684449482232295,"score_spread":0.2459090759551105,"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."}}