{"id":"W6893439100","doi":"10.5281/zenodo.2579386","title":"GEM-MACH CFFEPS rev m3848_CFFEPS","year":2019,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Air quality index; Executable; Biomass burning; Quality (philosophy); Software; Source code; Government (linguistics); Code (set theory)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001166825,0.001669386,0.001287307,0.001233444,0.001700195,0.00279025,0.005230315,0.002380644,0.375613],"category_scores_gemma":[0.005364408,0.001759641,0.002048398,0.001839265,0.0006972987,0.004513896,0.003038007,0.003057686,0.3566782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003703683,"about_ca_system_score_gemma":0.004083547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0948334,"about_ca_topic_score_gemma":0.06997668,"domain_scores_codex":[0.9990155,0.00007339322,0.00005653978,0.000187041,0.0004982057,0.0001694029],"domain_scores_gemma":[0.9980387,0.0002092895,0.00008657508,0.0004764691,0.001008495,0.000180482],"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":[0.00007555202,0.00001604746,0.0005159662,0.0002347002,0.00001785816,0.00003805572,0.00006443229,0.001722854,0.0007611068,0.004302058,0.9783278,0.0139237],"study_design_scores_gemma":[0.0001017864,0.00001185696,0.001015197,0.00009189654,0.0000125582,0.00005843132,0.00003525058,0.005718104,0.002799971,0.002796833,0.9873118,0.00004621915],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003258524,0.0005253778,0.04308409,0.001274286,0.0008569179,0.0005310112,0.3749888,0.3697082,0.2057728],"genre_scores_gemma":[0.0214504,0.0006823657,0.06255481,0.00124935,0.0001944063,0.0007670683,0.4868928,0.3103543,0.1158546],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.375613,"threshold_uncertainty_score":0.8906122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03305128398717389,"score_gpt":0.2510825022855473,"score_spread":0.2180312182983734,"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."}}