{"id":"W2988561754","doi":"10.1130/abs/2019am-339493","title":"DIACHRONOUS COLLISION AT THE LAURENTIAN MARGIN DURING APPALACHIAN-CALEDONIDE OROGENESIS","year":2019,"lang":"en","type":"article","venue":"Abstracts with programs - Geological Society of America","topic":"Mineralogy and Gemology Studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Diachronous; Margin (machine learning); Geology; Collision; Computer science; Seismology; Computer security; Tectonics; Machine learning","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":[0.0003095537,0.0001335211,0.000182307,0.0007627288,0.00275348,0.00124978,0.0002894897,0.0005493991,0.003330704],"category_scores_gemma":[0.0007368557,0.0001397761,0.0001219048,0.0007320773,0.0009219434,0.0005262225,0.001794444,0.0004712902,0.0003602061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002695867,"about_ca_system_score_gemma":0.001897535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2261015,"about_ca_topic_score_gemma":0.4966779,"domain_scores_codex":[0.9998466,0.0000154377,0.00000734342,0.00002605182,0.00001942032,0.00008503392],"domain_scores_gemma":[0.9998264,0.00002510528,0.00004143712,0.00001002585,0.00004628194,0.00005082771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001030626,0.00008016583,0.9420692,0.0001118533,0.00008204734,0.004972327,0.01172069,0.001678494,0.01144587,0.006373434,0.001161172,0.01927408],"study_design_scores_gemma":[0.00001042307,0.00002368743,0.9915937,0.00002462666,0.000009030607,0.0001565599,0.003942906,0.0002559853,0.00022219,0.0001619159,0.003593442,0.000005453671],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955094,0.0001272568,0.00003460295,0.00009380688,0.000006850486,0.000003787952,0.00006164239,0.00000260255,0.00416001],"genre_scores_gemma":[0.9990857,0.00006261091,0.00002031613,0.00001604694,0.000004045362,0.000002294972,0.00006619075,0.000001704304,0.0007411963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2261015,"threshold_uncertainty_score":0.4495709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01045159889135893,"score_gpt":0.2062522233495625,"score_spread":0.1958006244582036,"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."}}