{"id":"W4394180351","doi":"10.6084/m9.figshare.23567034.v1","title":"Dataset of dissolved inorganic nitrogen data and dissolved inorganic carbon data in stations in the Canada Basin and the Chukchi shelf during 2010-2014 Chinese Arctic Scientific Expedition (CHINARE).xlsx","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Methane Hydrates and Related Phenomena","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arctic; The arctic; Oceanography; Dissolved organic carbon; Structural basin; Canada Basin; Environmental science; Carbon fibers; Geology; Materials science; Paleontology","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":[0.0005581803,0.001494736,0.001173079,0.003584869,0.001047352,0.001648476,0.00206805,0.001084779,0.09241733],"category_scores_gemma":[0.003038508,0.0008249871,0.000893438,0.01024488,0.000369341,0.0008755757,0.001206573,0.001263471,0.04547182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003806171,"about_ca_system_score_gemma":0.009107945,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4800031,"about_ca_topic_score_gemma":0.6010559,"domain_scores_codex":[0.9995083,0.00002978752,0.00005954304,0.000130298,0.0001413863,0.0001306104],"domain_scores_gemma":[0.9978381,0.0003848173,0.0001611245,0.0002445536,0.001099875,0.0002715956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006111313,0.0000119972,0.002360663,0.0007085458,0.00004186048,0.00002372554,0.00002867318,0.0003771254,0.0001057892,0.0002945805,0.994186,0.00179995],"study_design_scores_gemma":[0.0003809451,0.0000144208,0.03879036,0.0005126939,0.00007968087,0.00005012582,0.0001970278,0.0007145992,0.000564235,0.0006388843,0.9579926,0.00006444563],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004080067,0.000006300032,0.000007807178,0.000006750334,0.000003348453,0.000002037691,0.9997956,0.00003254865,0.0001046581],"genre_scores_gemma":[0.0002918073,0.00001935722,0.00007797904,0.000008980525,0.000001687867,0.00002249228,0.999221,0.00002294051,0.0003338168],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5199969,"threshold_uncertainty_score":0.9544184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02163321093081494,"score_gpt":0.2446352714282218,"score_spread":0.2230020604974069,"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."}}