{"id":"W6948076463","doi":"10.5065/d6bp00v4","title":"SBI Microzooplankton Grazing Data (ASCII). Version 1.0","year":2007,"lang":"en","type":"dataset","venue":"Earth Observing Laboratory","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arctic; Phytoplankton; Grazing; Beaufort sea; Zooplankton; Spring (device); Grazing pressure","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":[0.0009707387,0.001964935,0.001228027,0.003964876,0.0004620904,0.001278748,0.001985773,0.0008695244,0.02456695],"category_scores_gemma":[0.002759614,0.0008699226,0.0008745639,0.007000623,0.0001939463,0.0006728416,0.001194156,0.00106873,0.0259013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00115651,"about_ca_system_score_gemma":0.001633697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04756059,"about_ca_topic_score_gemma":0.05288385,"domain_scores_codex":[0.9993033,0.00007038892,0.0001550394,0.0001703174,0.0001862429,0.0001148125],"domain_scores_gemma":[0.9978164,0.0002343962,0.0005511786,0.000416884,0.0007824786,0.000198628],"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":[0.0002174691,0.00008796514,0.02250489,0.001224823,0.0001600638,0.00007991699,0.0001113086,0.001215779,0.000673463,0.0004404631,0.9669001,0.006383874],"study_design_scores_gemma":[0.0006741891,0.00006108302,0.1426169,0.0002975141,0.0001454757,0.0001171206,0.0002452711,0.00295007,0.002180225,0.0008013675,0.8498327,0.00007812943],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005983211,0.00001050819,0.00005084039,0.00001037609,0.000005381573,0.0000122318,0.998931,0.000138806,0.0002425503],"genre_scores_gemma":[0.0008050096,0.00001229608,0.0002025334,0.000007023715,0.000002370157,0.00007978119,0.998567,0.00002718916,0.0002967885],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04756059,"threshold_uncertainty_score":0.09456754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04154157810978471,"score_gpt":0.2713216230666069,"score_spread":0.2297800449568222,"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."}}