{"id":"W2951332731","doi":"10.2110/jsr.2019.29","title":"A New Approach To Quantify the Ordering State of Protodolomite Using XRD, TEM, and Z-Contrast Imaging","year":2019,"lang":"en","type":"article","venue":"Journal of Sedimentary Research","topic":"High-pressure geophysics and materials","field":"Earth and Planetary Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Contrast (vision); Geology; Mineralogy; Artificial intelligence; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003256903,0.000424302,0.0001718235,0.001448346,0.000215657,0.0006193839,0.0004121727,0.0002388342,0.0006311523],"category_scores_gemma":[0.000320908,0.0002685448,0.0001125223,0.0006214029,0.000297297,0.0003677376,0.0002511889,0.0003086628,0.0001415249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006712974,"about_ca_system_score_gemma":0.0005522733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01212932,"about_ca_topic_score_gemma":0.0391444,"domain_scores_codex":[0.9998847,0.00001055919,0.000009338984,0.00003116431,0.00005438544,0.000009943184],"domain_scores_gemma":[0.9997157,0.00004431796,0.00004349486,0.00002354071,0.0001538396,0.00001904742],"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":[0.00003629167,0.00002275235,0.008077532,0.0000993073,0.00002084103,0.00003873602,0.00006665428,0.001147335,0.9767293,0.0006932599,0.00007841938,0.01298947],"study_design_scores_gemma":[0.00001960693,0.000114681,0.07860493,0.00003331296,0.00005917736,0.0004075889,0.0003552288,0.1281387,0.7867246,0.0007209323,0.004779581,0.00004172961],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6082464,0.0008829332,0.3841684,0.00007266168,0.00002628256,0.0002151313,0.00117213,0.0008328157,0.004383282],"genre_scores_gemma":[0.6098104,0.0005303472,0.3874594,0.0000415772,0.000006392216,0.0001165088,0.0004439467,0.0000504564,0.001541051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01212932,"threshold_uncertainty_score":0.02411741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06347511855171091,"score_gpt":0.3236723447647309,"score_spread":0.26019722621302,"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."}}