{"id":"W2752659327","doi":"10.1063/1.5001451","title":"Deployment and early results from the CanSIM (Canadian Solar Spectral Irradiance Meter) network","year":2017,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Spectra Energy (Canada); University of Ottawa","funders":"Environment and Climate Change Canada; Public Works and Government Services Canada; Government of Canada","keywords":"Pyranometer; Irradiance; Spectroradiometer; Environmental science; Remote sensing; Solar irradiance; Atmospheric sciences; Meteorology; Physics; Geography; Optics; Reflectivity","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004314819,0.0001823028,0.0001697914,0.00003600219,0.00108364,0.002327211,0.001595095,0.00009001427,0.00000829875],"category_scores_gemma":[0.0002588094,0.0001480045,0.00003476993,0.0001223576,0.000138131,0.0009148769,0.0001698462,0.0002743005,0.00002947932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006417417,"about_ca_system_score_gemma":0.0003102399,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1006132,"about_ca_topic_score_gemma":0.044537,"domain_scores_codex":[0.9985351,0.00001525703,0.0002250332,0.0005006639,0.0002301989,0.0004937638],"domain_scores_gemma":[0.9986532,0.00008470927,0.0002149486,0.000522853,0.0001647105,0.0003596261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000556589,0.00002509996,0.779498,0.00001019879,0.0001082658,0.00002844096,0.02158488,0.000003909947,0.001456069,0.1405785,0.02919053,0.02746043],"study_design_scores_gemma":[0.0006243527,0.00009212836,0.9043228,0.00006501549,0.0000168133,0.000009182124,0.0001013679,0.03852173,0.0004406055,0.0153669,0.04008644,0.0003526427],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9248612,0.0005091103,0.01388675,0.03626222,0.001525866,0.0008912523,0.000109594,0.000281412,0.02167262],"genre_scores_gemma":[0.9937215,0.0001040661,0.003982188,0.001693004,0.0002938595,0.00001697417,0.000002704648,0.00001140309,0.0001742535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1252116,"threshold_uncertainty_score":0.9987085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03180121195358573,"score_gpt":0.237726940189619,"score_spread":0.2059257282360333,"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."}}