{"id":"W7107871071","doi":"10.20383/103.01513","title":"Mount Fidelity historical weather station datasets, Glacier National Park, British Columbia, Canada.","year":2025,"lang":"","type":"dataset","venue":"Federated Research Data Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weather station; Glacier; Mount; Automatic weather station; Surface weather observation; National weather service","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":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","open_science","research_integrity"],"category_scores_codex":[0.02099762,0.001687264,0.002560802,0.001163476,0.01294676,0.02445069,0.01245616,0.002509215,0.003404323],"category_scores_gemma":[0.02428224,0.002897931,0.0002571074,0.005728027,0.001641959,0.004130487,0.01298239,0.01188165,0.0005916985],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1546711,"about_ca_system_score_gemma":0.1930474,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9990398,"about_ca_topic_score_gemma":0.9987906,"domain_scores_codex":[0.9445184,0.01506601,0.005170674,0.008780841,0.0217241,0.004739928],"domain_scores_gemma":[0.9655985,0.004365825,0.001827104,0.01160083,0.0141346,0.002473175],"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":[0.0008007648,0.002081449,0.0003705896,0.001558274,0.001918791,0.007085532,0.00001509673,0.00006731416,0.0005186418,0.000005067818,0.9851869,0.00039159],"study_design_scores_gemma":[0.002428317,0.000230611,0.002498307,0.001728553,0.0004405172,0.000833424,0.0002221653,0.005550774,0.00003770721,0.00003263403,0.983631,0.002366022],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004525083,0.006693379,0.00004449841,0.0004388583,0.005786443,0.004517212,0.9803129,0.0001888059,0.001565329],"genre_scores_gemma":[0.001338678,0.001715328,0.000208131,0.0004143897,0.002533371,0.0007867615,0.941654,0.0002947921,0.0510545],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04948917,"threshold_uncertainty_score":0.9995874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07293210334521637,"score_gpt":0.3550019615140518,"score_spread":0.2820698581688355,"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."}}