{"id":"W6930024184","doi":"10.5065/d6pk0d8j","title":"Chukchi Sea Sediment Core Lipid Analysis, Station F9 (ASCII). Version 1.0","year":2007,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Caveolin-1 and cellular processes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Sediment core; Core (optical fiber); Sediment; Seawater; ASCII; Data set","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":[0.0008634116,0.002320486,0.001503045,0.004153109,0.0008940886,0.001637395,0.002961736,0.001241754,0.02444423],"category_scores_gemma":[0.002504046,0.0008799856,0.0009530894,0.007367523,0.0003775373,0.0006140451,0.001649932,0.001412484,0.03570582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001408159,"about_ca_system_score_gemma":0.003562332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04563382,"about_ca_topic_score_gemma":0.08370802,"domain_scores_codex":[0.9994765,0.00004198855,0.00007423214,0.0001483336,0.0001309868,0.0001279844],"domain_scores_gemma":[0.9984692,0.0002233756,0.000233044,0.0004056631,0.0004537331,0.0002150277],"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":[0.0004280599,0.00006987333,0.008079398,0.001746248,0.0001834459,0.000128592,0.00009717859,0.0008704111,0.001345027,0.0005029921,0.9789933,0.007555429],"study_design_scores_gemma":[0.0006148254,0.00004468541,0.07130399,0.0003386041,0.0001977377,0.000123022,0.0002022395,0.0009989804,0.002943918,0.0009079375,0.9222313,0.00009275922],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003112653,0.00001056701,0.0000331864,0.000006981921,0.00000322179,0.000005670527,0.9993435,0.0001168214,0.0001686928],"genre_scores_gemma":[0.0004658996,0.00001196885,0.0001670684,0.000005736806,0.00000110752,0.00004121348,0.9990214,0.00003210003,0.0002535484],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04563382,"threshold_uncertainty_score":0.09073639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02194855850887055,"score_gpt":0.3161350814685639,"score_spread":0.2941865229596934,"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."}}