{"id":"W7146588358","doi":"","title":"OMTI All-Sky Imager Quick-Look Data (OI emission, 557.7nm, 15s) at Eureka, Canada","year":2017,"lang":"en","type":"dataset","venue":"Institutional Repositories DataBase (IRDB)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thermosphere; Filter (signal processing); Mesosphere; Instrumentation (computer programming); Night sky","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","sts","open_science","insufficient_payload"],"category_scores_codex":[0.001953701,0.002640575,0.002133389,0.0005727353,0.005690929,0.001585518,0.01176424,0.001169715,0.001708638],"category_scores_gemma":[0.009409689,0.002596201,0.0003666593,0.0006336886,0.002787966,0.00515064,0.01475054,0.003009192,0.006328266],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.007196499,"about_ca_system_score_gemma":0.03213799,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.785612,"about_ca_topic_score_gemma":0.7944025,"domain_scores_codex":[0.9824396,0.0005836425,0.002735573,0.00501213,0.006836728,0.002392335],"domain_scores_gemma":[0.9714741,0.0007344679,0.003053437,0.02103409,0.001635593,0.002068342],"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":[0.0007110224,0.0004393003,0.0005176101,0.0007123103,0.0009379936,0.01346177,0.00001591716,0.00003171006,0.003287353,0.0002543582,0.9795833,0.00004732917],"study_design_scores_gemma":[0.001519313,0.00005468879,0.0003388239,0.001635179,0.001261509,0.003075952,0.00002496374,0.00004825611,0.001839453,0.0000212831,0.9873652,0.002815391],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003847134,0.003743632,0.00003747177,0.0006337886,0.02170389,0.001400241,0.9694856,0.0003746693,0.002235967],"genre_scores_gemma":[0.0001681544,0.0005388592,0.001091871,0.0008411173,0.009474914,0.0002377147,0.9797258,0.0003351095,0.007586445],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02494149,"threshold_uncertainty_score":0.9999259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04437555750863199,"score_gpt":0.3202740958245275,"score_spread":0.2758985383158956,"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."}}