{"id":"W6925831778","doi":"10.21233/sne3-1m81","title":"Ottawa River ostracode surface sample dataset","year":2018,"lang":"en","type":"dataset","venue":"Neotoma Paleoecological Database","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sample (material); Paleoecology; Hydrology (agriculture); Surface (topology); Raw data","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":[0.0004502712,0.001143267,0.0008860594,0.002918795,0.0009554452,0.001307344,0.001934451,0.0008930179,0.02359403],"category_scores_gemma":[0.002901657,0.0005046221,0.000763512,0.005708833,0.0005245221,0.0006323303,0.001165351,0.001086956,0.02026335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005790696,"about_ca_system_score_gemma":0.009368999,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6495708,"about_ca_topic_score_gemma":0.8617076,"domain_scores_codex":[0.9993762,0.00004660392,0.00007189289,0.0001503317,0.0002059286,0.0001490083],"domain_scores_gemma":[0.9970526,0.0002729229,0.0002000498,0.0004634339,0.001704557,0.0003064622],"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":[0.0001141196,0.00002638162,0.005292101,0.0003669825,0.00005251849,0.0000364157,0.00006153457,0.0006543806,0.0002699727,0.000382303,0.9895079,0.003235405],"study_design_scores_gemma":[0.0001522081,0.00001589349,0.05618062,0.0002407339,0.00007202125,0.00005765244,0.0003534388,0.001222612,0.00089929,0.0004812596,0.9402503,0.00007396779],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005856921,0.00002360249,0.00002888905,0.00002271388,0.00000836065,0.0000128611,0.9988023,0.0001062639,0.0004093312],"genre_scores_gemma":[0.001305074,0.00002491231,0.0001757671,0.00001152353,0.00000223514,0.00006436743,0.9975131,0.00003098514,0.0008721538],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3504292,"threshold_uncertainty_score":0.704986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1328001093702441,"score_gpt":0.3985061333075233,"score_spread":0.2657060239372792,"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."}}