{"id":"W6947994255","doi":"10.4224/40001880","title":"Archive of NRC Twin Otter data from 1991-2003 flux projects","year":2003,"lang":"en","type":"report","venue":"NPARC","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Flux (metallurgy); Data collection; Hydrology (agriculture); Otter","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003488093,0.0006570864,0.0006148671,0.008870839,0.001440406,0.002158087,0.00147054,0.0005242305,0.01391791],"category_scores_gemma":[0.01259933,0.0004027594,0.0003311978,0.01647831,0.000375188,0.00125046,0.001045283,0.0007737366,0.0126701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004419622,"about_ca_system_score_gemma":0.009696683,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.376031,"about_ca_topic_score_gemma":0.3242414,"domain_scores_codex":[0.995559,0.0002548324,0.0003826998,0.0004655749,0.003101204,0.0002366788],"domain_scores_gemma":[0.9825071,0.001081276,0.001130301,0.004492881,0.01024509,0.000543468],"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":[0.0004851849,0.0001546477,0.02591106,0.0004310368,0.00007322836,0.0001573419,0.0008058643,0.002600336,0.003682894,0.004289088,0.8834351,0.07797433],"study_design_scores_gemma":[0.00008215269,0.0000313133,0.09276785,0.0001225869,0.00004070881,0.0000993643,0.0003175766,0.001322361,0.003663713,0.000765644,0.9007338,0.00005283538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01536096,0.000248535,0.002170138,0.0003262017,0.00008275012,0.000236854,0.9490138,0.002991808,0.02956906],"genre_scores_gemma":[0.01239024,0.0002664743,0.0050722,0.00004411113,0.00002375053,0.0002534922,0.9742261,0.0005631487,0.007160527],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6239691,"threshold_uncertainty_score":0.7476844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.223025717634517,"score_gpt":0.3894101678332731,"score_spread":0.1663844501987561,"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."}}