{"id":"W6925061765","doi":"10.1594/pangaea.952319","title":"XRF scanning data of sediment core MSM12/2-5-1","year":2009,"lang":"en","type":"dataset","venue":"Publishing Network for Geoscientific and Environmental Data (PANGAEA) (Alfred Wegener Institute for Polar and Marine Research)","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Sediment core; Core (optical fiber); Sediment; Calibration; Table (database)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009303826,0.00175524,0.001127297,0.004542395,0.0006611418,0.001437679,0.002349529,0.001557013,0.02112834],"category_scores_gemma":[0.003602448,0.000670462,0.001295964,0.008035742,0.000287275,0.0008260608,0.001348717,0.001113053,0.04037484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001491351,"about_ca_system_score_gemma":0.002280229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06381195,"about_ca_topic_score_gemma":0.1071227,"domain_scores_codex":[0.9992162,0.00007811681,0.0001252769,0.0001974036,0.0002486656,0.0001342611],"domain_scores_gemma":[0.9981535,0.0001554901,0.000282066,0.0003390848,0.0009296038,0.0001400765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001602432,0.0000505001,0.004646735,0.0005637934,0.00005749894,0.00006451426,0.00003187691,0.0004047881,0.0003524665,0.0002099963,0.9894393,0.004018284],"study_design_scores_gemma":[0.0004862197,0.0000357197,0.06101724,0.0002865068,0.00006499822,0.0001406016,0.0001593019,0.0007005082,0.00102548,0.000546929,0.9354829,0.00005373685],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005857131,0.0000453251,0.00003595409,0.00003105642,0.00001148553,0.00001270859,0.9986489,0.0001864707,0.0004423212],"genre_scores_gemma":[0.0006317862,0.0000276658,0.0001887239,0.00001195067,0.00000427457,0.00004405692,0.9986051,0.0000283766,0.0004581319],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06381195,"threshold_uncertainty_score":0.1268811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1183654696781885,"score_gpt":0.2954493865040124,"score_spread":0.1770839168258239,"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."}}