{"id":"W4392620357","doi":"10.5194/egusphere-egu24-16240","title":"Insights into the tectonic evolution of the northern Norwegian passive margin: Integrating field observations and plate modeling over 200 million years.","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Geological formations and processes","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Norwegian; Margin (machine learning); Field (mathematics); Tectonics; Geology; Plate tectonics; Passive margin; Paleontology; Seismology; Geography; Computer science; Rift","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":[0.0006206317,0.0004042947,0.0002778857,0.0007856034,0.0002606373,0.0005188084,0.0005562903,0.0005065703,0.001006566],"category_scores_gemma":[0.00115825,0.0003931678,0.0007532566,0.0009933264,0.0002670723,0.0006089287,0.0003034426,0.0003020726,0.0003867663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001033656,"about_ca_system_score_gemma":0.0007342148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2104612,"about_ca_topic_score_gemma":0.2408883,"domain_scores_codex":[0.9998683,0.00002079631,0.0000159278,0.00005654574,0.00002356977,0.00001481025],"domain_scores_gemma":[0.9997279,0.00006980449,0.00008724496,0.00004573884,0.00004868563,0.00002051739],"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":[0.0001177624,0.00008983679,0.5015091,0.0001932954,0.000540923,0.0003914374,0.0005513233,0.4598925,0.002490062,0.001233543,0.002707175,0.03028306],"study_design_scores_gemma":[0.0000269186,0.00007359912,0.4600356,0.00009382801,0.0001576792,0.0001664387,0.0005008914,0.5280359,0.0006148367,0.0008463782,0.009402741,0.00004521459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982501,0.00217493,0.003803635,0.0002298287,0.00005496669,0.00001268675,0.008314736,0.0001905367,0.002717763],"genre_scores_gemma":[0.9876407,0.0007651421,0.003043448,0.00002379796,0.00001640626,0.00001707443,0.007685582,0.00003950375,0.0007685212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2104612,"threshold_uncertainty_score":0.4184722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01841801531934743,"score_gpt":0.2114992266748772,"score_spread":0.1930812113555298,"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."}}