{"id":"W4408326599","doi":"10.1029/2024gc012124","title":"A Machine Learning Approach to Single Garnet Geothermometry and Application to Tracing the Fingerprint of Superdeep Diamonds","year":2025,"lang":"en","type":"article","venue":"Geochemistry Geophysics Geosystems","topic":"Geological and Geochemical Analysis","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; De Beers (Canada); University of Alberta","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Society of Economic Geologists Canada Foundation","keywords":"Geology; Fingerprint (computing); Tracing; Geochemistry; Seismology; Artificial intelligence; Computer science","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":[0.0003207766,0.0002032966,0.0003500053,0.00006514887,0.0001786987,0.00005825873,0.0003357354,0.00008799889,0.000127836],"category_scores_gemma":[0.0001325345,0.000141839,0.00009876445,0.0008954114,0.0000743842,0.00003718555,0.00008802651,0.0002223309,0.00003382147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007343599,"about_ca_system_score_gemma":0.00001635521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005168888,"about_ca_topic_score_gemma":0.0001835228,"domain_scores_codex":[0.9985624,0.00005804051,0.0003409679,0.000463811,0.0002424193,0.0003323757],"domain_scores_gemma":[0.9991025,0.0002198826,0.0000986579,0.0003377232,0.00008850795,0.000152754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001577576,0.000385954,0.4377045,0.001245766,0.0003162744,0.000003047244,0.001548265,0.1568913,0.2928329,0.000507418,0.0001720143,0.1082349],"study_design_scores_gemma":[0.0009194587,0.0004167243,0.2926627,0.000358347,0.0003991189,0.00002896634,0.002755952,0.5550686,0.1217893,0.01490355,0.009166361,0.001530956],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766404,0.0006899946,0.005243635,0.0004180298,0.00003376913,0.0002788422,0.00004947744,0.00004164489,0.01660418],"genre_scores_gemma":[0.9987499,0.000009062928,0.0003068577,0.0001801956,0.00007746111,0.00002020283,0.000131893,0.000003423792,0.000521059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3981772,"threshold_uncertainty_score":0.7813846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00584672708178755,"score_gpt":0.1820430651128111,"score_spread":0.1761963380310236,"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."}}