{"id":"W7018664293","doi":"","title":"Dont Mess with Texas: Getting the Lone Star State to Net-Zero by 2050","year":2022,"lang":"en","type":"report","venue":"Issue Lab (Candid)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workforce; State (computer science); Product (mathematics); Resource (disambiguation); Global Leadership; Natural resource; Energy (signal processing); Face (sociological concept)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001046584,0.0006912473,0.0001915113,0.0004849013,0.00704309,0.00824022,0.0007984811,0.002934946,0.08164298],"category_scores_gemma":[0.002300209,0.0002586167,0.0003572413,0.0005607918,0.002545358,0.008221738,0.004895484,0.006177684,0.02204847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002946122,"about_ca_system_score_gemma":0.009330138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0150468,"about_ca_topic_score_gemma":0.03704217,"domain_scores_codex":[0.9995247,0.00008401867,0.00001275301,0.00005456932,0.0001255138,0.0001985316],"domain_scores_gemma":[0.9988412,0.00005465061,0.00004562894,0.0000504152,0.0002349643,0.0007732031],"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":[0.00003032553,0.00004029793,0.0007290965,0.0000687006,0.000004483107,0.000101614,0.0005761699,0.0001179033,0.0002248223,0.02541751,0.9269583,0.04573075],"study_design_scores_gemma":[0.000007733795,0.00004133309,0.0007740356,0.0001781267,0.000005104872,0.00005860386,0.002713734,0.0001087881,0.0001828434,0.008972794,0.9869425,0.00001433209],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.01441329,0.007541917,0.003546194,0.6326274,0.02355111,0.00006941733,0.001208014,0.001068217,0.3159745],"genre_scores_gemma":[0.1756436,0.02367799,0.0125811,0.2324202,0.005425555,0.0002185225,0.003176163,0.001139194,0.5457177],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.08164298,"threshold_uncertainty_score":0.273123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01605535764832396,"score_gpt":0.2780341223887622,"score_spread":0.2619787647404382,"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."}}