{"id":"W3205348916","doi":"10.1029/2021ef002399","title":"Scaling Deep Decarbonization Technologies","year":2021,"lang":"en","type":"article","venue":"Earth s Future","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Energy Regulator","funders":"National Academy of Sciences; Alfred P. Sloan Foundation","keywords":"Resource (disambiguation); Renewable energy; Business; Emerging technologies; Climate change mitigation; Climate change; Environmental economics; Natural resource economics; Environmental resource management; Environmental science; Economics; Engineering; Computer science","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":[0.00197258,0.0008902531,0.0004196853,0.001081756,0.0007822038,0.00284868,0.0009876837,0.00108637,0.007659188],"category_scores_gemma":[0.003257252,0.0002442747,0.0005509644,0.001166352,0.001270229,0.005124731,0.004601316,0.002300927,0.001597011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002248891,"about_ca_system_score_gemma":0.002464576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002754066,"about_ca_topic_score_gemma":0.00254982,"domain_scores_codex":[0.9984624,0.0002369852,0.00007599479,0.00021462,0.0007349793,0.0002750015],"domain_scores_gemma":[0.9977973,0.0006007334,0.0001985242,0.0003804015,0.0008630936,0.0001600172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001212554,0.0003071544,0.004192188,0.001096294,0.0001058533,0.0003502492,0.0007608469,0.05181558,0.03659388,0.4387945,0.0322958,0.4335665],"study_design_scores_gemma":[0.00005846606,0.0005453411,0.004413728,0.0007878355,0.0001202108,0.0002815439,0.002158766,0.04398173,0.03758634,0.4171748,0.4927959,0.0000952811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2353633,0.03032903,0.2148769,0.0366178,0.003948144,0.0008091783,0.001352519,0.001335152,0.4753679],"genre_scores_gemma":[0.8999857,0.02239683,0.04665427,0.005101212,0.0005244838,0.0003603621,0.0006332941,0.0001770115,0.02416682],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007659188,"threshold_uncertainty_score":0.02562255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002649214037660687,"score_gpt":0.1930568913208161,"score_spread":0.1904076772831554,"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."}}