{"id":"W3080497521","doi":"10.1016/j.epsl.2020.116495","title":"Magnetite biomineralization in ferruginous waters and early Earth evolution","year":2020,"lang":"en","type":"article","venue":"Earth and Planetary Science Letters","topic":"Geomagnetism and Paleomagnetism Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canada Research Chairs; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Magnetite; Authigenic; Geology; Precambrian; Biomineralization; Water column; Anoxic waters; Geochemistry; Mineral; Lepidocrocite; Mineralogy; Earth science; Paleontology; Chemistry; Diagenesis; Ecology; Biology; Oceanography; Goethite","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001104087,0.0001196402,0.00009905633,0.00007493998,0.0001202302,0.0000542117,0.00009105824,0.00004102188,0.000008855777],"category_scores_gemma":[0.00002079714,0.000111102,0.00001230309,0.0001793531,0.0003359014,0.00002394148,0.00005884796,0.00005950546,0.000007691443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000011257,"about_ca_system_score_gemma":0.00001577251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002910361,"about_ca_topic_score_gemma":0.0001265615,"domain_scores_codex":[0.9990813,0.00003003832,0.0001177842,0.0003725956,0.0001273228,0.00027102],"domain_scores_gemma":[0.999735,0.000006160451,0.00002739893,0.00008840857,0.00001050901,0.0001325205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004533037,0.000004209499,0.5300456,0.0000178599,0.000003098079,0.00001564485,0.0003805699,0.0002059479,0.4675013,0.00001193117,0.0002776171,0.001490826],"study_design_scores_gemma":[0.0003948946,0.0004229856,0.9931401,0.000006859142,0.000004741508,0.00001977943,0.00003802505,0.0004510402,0.001566223,0.000005317479,0.003789182,0.0001608272],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948245,0.001433193,0.0001259899,0.003195492,0.00007383792,0.0001278116,0.00001358025,0.000009810758,0.0001958354],"genre_scores_gemma":[0.996938,0.0002659267,0.0004847406,0.002108953,0.00008327539,0.000002246735,0.00005010305,0.000004117067,0.00006261613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4659351,"threshold_uncertainty_score":0.4530608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006418265603127418,"score_gpt":0.176122143284077,"score_spread":0.1697038776809496,"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."}}