{"id":"W4398360605","doi":"10.7910/dvn/mapgnu","title":"Replication Data for: Satellite discovery of anomalously large methane point sources from oil/gas production","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"GHGSat (Canada)","funders":"","keywords":"Replication (statistics); Methane; Satellite; Point (geometry); Fossil fuel; Production (economics); Astrobiology; Environmental science; Physics; Chemistry; Astronomy; Engineering; Biology; Waste management; Economics; Mathematics","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":[0.0009556695,0.001425924,0.001044938,0.002021004,0.0009111093,0.001565693,0.002265029,0.001415731,0.05949378],"category_scores_gemma":[0.004559341,0.0005893762,0.001264526,0.004346503,0.0004481079,0.001306418,0.0017641,0.001684643,0.05563413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001176053,"about_ca_system_score_gemma":0.002691119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03149516,"about_ca_topic_score_gemma":0.05616539,"domain_scores_codex":[0.9991911,0.00009295993,0.00009753821,0.0002565005,0.0002319286,0.0001300143],"domain_scores_gemma":[0.998164,0.000273623,0.0001898557,0.000608148,0.000548844,0.0002154903],"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":[0.00008329916,0.00001411105,0.001409475,0.0003817198,0.00004251739,0.00002542822,0.00002209533,0.0003346301,0.0003955691,0.000525707,0.9954633,0.001302221],"study_design_scores_gemma":[0.000381848,0.00001714941,0.008672887,0.0001709526,0.00004727871,0.00005703988,0.00009578026,0.0005892005,0.001401878,0.001669249,0.9868543,0.00004238954],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002109222,0.00002438656,0.00006616687,0.00005621748,0.00002745667,0.000007709985,0.9986873,0.000360736,0.0005590337],"genre_scores_gemma":[0.0006944579,0.00002555168,0.0002506936,0.0000376235,0.000008311231,0.00003194378,0.998341,0.0001419009,0.0004685559],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05949378,"threshold_uncertainty_score":0.1990265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01844614366009651,"score_gpt":0.2400774692766652,"score_spread":0.2216313256165687,"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."}}