{"id":"W4223954608","doi":"10.21203/rs.3.rs-1551516/v1","title":"Dating dirty speleothems using paleomagnetism","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Fundação para a Ciência e a Tecnologia; Ministerio de Ciencia, Innovación y Universidades","keywords":"Archaeomagnetic dating; Stalagmite; Paleomagnetism; Geology; Speleothem; Secular variation; Radiometric dating; Cave; Paleontology; Series (stratigraphy); Geophysics; Archaeology; Earth's magnetic field; Geography; Holocene","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":[0.0005149051,0.0005992268,0.0003384397,0.001938358,0.0004224829,0.001128762,0.0003391019,0.000394912,0.0008020075],"category_scores_gemma":[0.0007882527,0.0002298387,0.0002914076,0.001370966,0.0004155124,0.0003583536,0.0004233099,0.000177581,0.0003909809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005399699,"about_ca_system_score_gemma":0.0003828948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009682015,"about_ca_topic_score_gemma":0.03017781,"domain_scores_codex":[0.9997374,0.00005189992,0.00001268572,0.0001038133,0.00006332598,0.00003090509],"domain_scores_gemma":[0.9997182,0.00006007752,0.000082521,0.000057363,0.00005854473,0.00002332821],"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":[0.0004781269,0.00003897629,0.3955016,0.0003071245,0.0003009932,0.0004731848,0.0005766167,0.01222914,0.5003586,0.0009415339,0.0003284714,0.08846558],"study_design_scores_gemma":[0.00002010402,0.000170105,0.8503196,0.00008998773,0.0001168205,0.00073635,0.0003670806,0.04447747,0.08956239,0.001279895,0.01280263,0.00005765325],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9513518,0.001836066,0.04323544,0.00003545207,0.00002818279,0.00002965328,0.0007829012,0.0001568938,0.002543601],"genre_scores_gemma":[0.9827235,0.0006126629,0.01550091,0.00000835537,0.000008511815,0.00001155173,0.0002743253,0.00004253109,0.0008175775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009682015,"threshold_uncertainty_score":0.01925129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1307214997131114,"score_gpt":0.3945061450621366,"score_spread":0.2637846453490252,"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."}}