{"id":"W4376170986","doi":"10.2138/am-2022-8688","title":"Identifying serpentine minerals by their chemical compositions with machine learning","year":2023,"lang":"en","type":"article","venue":"American Mineralogist","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Geology; Geochemistry; Mineralogy; Ringwoodite; Chrysotile; Crust; Blueschist; Plagioclase; Subduction; Tectonics; Mantle (geology); Materials science; Quartz; Seismology; Paleontology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003729561,0.000593996,0.0003954739,0.00131113,0.0002557403,0.0005026234,0.0003816097,0.0004697073,0.0005835448],"category_scores_gemma":[0.0007484409,0.0002097562,0.000462451,0.00057146,0.0002332621,0.0003996512,0.0002662458,0.0003329853,0.0003606375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004120342,"about_ca_system_score_gemma":0.0002737888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004287469,"about_ca_topic_score_gemma":0.005362999,"domain_scores_codex":[0.9998626,0.00002457757,0.00000800545,0.00006055219,0.0000298357,0.0000144694],"domain_scores_gemma":[0.9996744,0.0001042322,0.00008046485,0.0000276556,0.00009173193,0.00002147116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000476359,0.0004109582,0.1641561,0.0001756478,0.0002646988,0.000249933,0.000129464,0.4650436,0.1737206,0.0006713982,0.0008451096,0.1938562],"study_design_scores_gemma":[0.000003480111,0.00002143786,0.008108785,0.000003266868,0.00000765619,0.0000143251,0.00001249758,0.9806927,0.01071837,0.0002560878,0.0001554013,0.000006056117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8956499,0.0003648308,0.101061,0.0001002658,0.00003128187,0.00005177003,0.0003154442,0.0009711756,0.001454288],"genre_scores_gemma":[0.9716882,0.00004935653,0.02774544,0.00001335223,0.000006394647,0.00001296374,0.0001539948,0.0000115472,0.0003188833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004287469,"threshold_uncertainty_score":0.008525074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551847291926166,"score_gpt":0.2388096277432085,"score_spread":0.2232911548239468,"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."}}