{"id":"W4296403802","doi":"","title":"Reconstruction of LGM tropical SST anomalies from Mg/Ca and UK37’ using the SENSETROP database","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Database; Geology; Computer science","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":[0.0003552868,0.0005818365,0.0005047519,0.002539189,0.0003918983,0.001047368,0.0008928507,0.001038876,0.005780493],"category_scores_gemma":[0.001549447,0.0004623659,0.0008141889,0.004437672,0.00035739,0.0006335423,0.0005794234,0.0004394439,0.003984442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009640239,"about_ca_system_score_gemma":0.001832456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1628366,"about_ca_topic_score_gemma":0.1721809,"domain_scores_codex":[0.9997427,0.00002189244,0.00002827783,0.000102449,0.00005084309,0.00005385625],"domain_scores_gemma":[0.9994337,0.0000497755,0.00008939763,0.0001506521,0.0002152395,0.00006118989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003228744,0.0003598742,0.317417,0.001850075,0.001800963,0.001670066,0.001325285,0.148964,0.02896269,0.006532466,0.3537593,0.1341295],"study_design_scores_gemma":[0.0008264714,0.00007877616,0.6699433,0.0003026819,0.0003673487,0.0003167868,0.0008112594,0.1423551,0.009484434,0.001783527,0.1735393,0.0001910446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.486835,0.0008135788,0.003317083,0.0004802968,0.0002793119,0.00006005436,0.4951872,0.005101903,0.007925574],"genre_scores_gemma":[0.5766264,0.0005025741,0.01086462,0.0001055293,0.00007485812,0.00009695836,0.4081657,0.0005904055,0.002973048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1628366,"threshold_uncertainty_score":0.3237776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039902066068546,"score_gpt":0.2157213197942529,"score_spread":0.2053222991335675,"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."}}