{"id":"W4312265783","doi":"10.46427/gold2022.10295","title":"Understanding trace element mobility during early diagenesis using several in situ techniques","year":2022,"lang":"en","type":"article","venue":"Goldschmidt2022 abstracts","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"In situ; Diagenesis; Trace element; TRACE (psycholinguistics); Geology; Computer science; Earth science; Geochemistry; Chemistry; Philosophy","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":[0.0001736002,0.0004489449,0.0003260464,0.0006517656,0.0005967848,0.0006224304,0.0004031661,0.000722722,0.001659666],"category_scores_gemma":[0.000260914,0.0002766428,0.0002933745,0.0003882517,0.0002515616,0.0008330668,0.0003560542,0.0005650398,0.0004260878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003974485,"about_ca_system_score_gemma":0.0003601814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00433558,"about_ca_topic_score_gemma":0.01194949,"domain_scores_codex":[0.9998791,0.000005901832,0.000005850126,0.0000523693,0.00003159341,0.00002515819],"domain_scores_gemma":[0.9998926,0.00003173973,0.00001699641,0.000008697408,0.0000413011,0.000008630679],"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":[0.00006526559,0.00001543932,0.002730523,0.00004759202,0.000009309063,0.0000342664,0.00009900307,0.0002692096,0.9912081,0.00009760937,0.00004480665,0.005378874],"study_design_scores_gemma":[0.00001061698,0.000149199,0.02047009,0.000009482042,0.00004309402,0.0001445364,0.000384988,0.004466938,0.9710103,0.000244721,0.003051291,0.00001482577],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9528702,0.000784628,0.04063485,0.0002007542,0.000044792,0.00004251756,0.0006045465,0.0002463328,0.004571327],"genre_scores_gemma":[0.971384,0.0008082642,0.0223181,0.00006655175,0.00001767881,0.00004393168,0.0003640481,0.00006545288,0.004931897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00433558,"threshold_uncertainty_score":0.008620679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05679657730880602,"score_gpt":0.2650761720935326,"score_spread":0.2082795947847266,"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."}}