{"id":"W6948238654","doi":"10.5065/d6hx19tr","title":"Beaufort Sea Sediment Core Lipid Analysis, Station 44 (Excel). Version 1.0","year":2007,"lang":"en","type":"dataset","venue":"Earth Observing Laboratory","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Beaufort sea; Sediment core; Core (optical fiber); Sediment; Data set; Buoy; Seabed; Sea ice","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":[0.001909452,0.002022774,0.001563109,0.005928956,0.0008210122,0.002170002,0.003247803,0.001050815,0.03623627],"category_scores_gemma":[0.004864633,0.001361264,0.001089517,0.01001126,0.0004429872,0.001042107,0.001556806,0.001648761,0.04634523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001629656,"about_ca_system_score_gemma":0.003705546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04345882,"about_ca_topic_score_gemma":0.05837733,"domain_scores_codex":[0.9988155,0.0001381414,0.0001867991,0.0003006911,0.000349657,0.000209097],"domain_scores_gemma":[0.9970424,0.0006575639,0.000431353,0.0007692504,0.0008535603,0.000245921],"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":[0.0002834908,0.00005341228,0.004040314,0.00130776,0.000143071,0.00007561048,0.000106637,0.0008632675,0.001021733,0.0007887386,0.9824577,0.008858222],"study_design_scores_gemma":[0.0003957185,0.00003552853,0.02916713,0.0002965613,0.00007632261,0.00007155773,0.0001097784,0.000615562,0.001908667,0.001129757,0.9661232,0.00007026958],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000248823,0.00001312666,0.000118042,0.00001054286,0.000004098847,0.0000109565,0.9987986,0.0003663235,0.0004295903],"genre_scores_gemma":[0.0004907839,0.00001997822,0.000575367,0.00001339635,0.00000208352,0.00007735012,0.9982386,0.0001552192,0.000427187],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04345882,"threshold_uncertainty_score":0.1212224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01502659045242053,"score_gpt":0.2540308779028368,"score_spread":0.2390042874504163,"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."}}