{"id":"W6911086022","doi":"10.5065/d6br8q8x","title":"SBI Microzooplankton Grazing Data (Excel). Version 1.0","year":2007,"lang":"en","type":"dataset","venue":"Earth Observing Laboratory","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arctic; Beaufort sea; Phytoplankton; Grazing; Zooplankton; Spring (device)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.003747363,0.001322123,0.001195163,0.001014295,0.0006495894,0.0004531349,0.005950816,0.001428399,0.00191896],"category_scores_gemma":[0.001168916,0.001495013,0.0001541827,0.002364695,0.000280519,0.001251643,0.00415075,0.00264544,0.05283336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003212203,"about_ca_system_score_gemma":0.001361715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009612645,"about_ca_topic_score_gemma":0.005515503,"domain_scores_codex":[0.9923742,0.0005969444,0.001156772,0.002436387,0.001755126,0.001680503],"domain_scores_gemma":[0.9877108,0.0004541333,0.001102565,0.009439418,0.0006715434,0.0006215496],"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":[0.0001091986,0.0001547637,0.0005313274,0.0005898515,0.0001803884,0.0006789014,0.00002415276,0.00001082982,0.004323618,0.000001710152,0.9932401,0.0001551364],"study_design_scores_gemma":[0.0008795802,0.00006550584,0.002155036,0.0009024784,0.0003582299,0.00001683705,0.00006029333,0.00003294237,0.0008252438,0.000003759505,0.9931856,0.001514503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003206627,0.006122241,0.000005884896,0.00004337351,0.003528857,0.000602569,0.9856403,0.0006922433,0.0001578702],"genre_scores_gemma":[0.00003132313,0.0004804128,0.001465541,0.001059932,0.001765664,0.00001096152,0.994603,0.0003939717,0.0001891407],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0509144,"threshold_uncertainty_score":0.999953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05047551522393952,"score_gpt":0.3006920556645555,"score_spread":0.250216540440616,"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."}}