{"id":"W6948049406","doi":"10.48322/7cw7-xg89","title":"Meanook (MEA) Ground-based Vector Magnetic Field (L2) 1.0 s Data","year":2023,"lang":"en","type":"dataset","venue":"Space Physics Data Facility","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Magnetic field; Field (mathematics); Longitude; Latitude; Earth's magnetic field","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":[0.0005345527,0.001585759,0.0009657637,0.001990454,0.0007126043,0.001680365,0.002583138,0.001556621,0.0538686],"category_scores_gemma":[0.003427338,0.0005846321,0.0008872578,0.005377437,0.000358595,0.001393322,0.001329783,0.001415259,0.08728577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001210107,"about_ca_system_score_gemma":0.001978879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05553016,"about_ca_topic_score_gemma":0.08955832,"domain_scores_codex":[0.9993377,0.00006738411,0.00005607588,0.0002348261,0.0001969882,0.0001068369],"domain_scores_gemma":[0.998546,0.000212842,0.0001529592,0.0004074651,0.0005574091,0.000123295],"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":[0.00003807281,0.00001239277,0.0008739889,0.0002201327,0.00002091355,0.00001261103,0.00001519475,0.0004793608,0.0001072357,0.000312425,0.9960406,0.001867062],"study_design_scores_gemma":[0.0001899618,0.00001339815,0.00694315,0.0001317234,0.0000260126,0.00002807463,0.00008256293,0.0009904832,0.0005620231,0.001527507,0.9894665,0.00003860553],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001288081,0.00001746453,0.00006213424,0.00002218376,0.00001165333,0.000003601695,0.9989927,0.000281855,0.0004795663],"genre_scores_gemma":[0.0005018919,0.00001840126,0.0002953679,0.00001903993,0.000004673338,0.0000288034,0.9985019,0.00009516727,0.0005348044],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05553016,"threshold_uncertainty_score":0.1802084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1090123540873449,"score_gpt":0.3346124983974054,"score_spread":0.2256001443100605,"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."}}