{"id":"W1656910747","doi":"10.1163/cl-2012-056","title":"Carbon capture and storage in the CDM: Finding its place among climate mitigation options?","year":2012,"lang":"en","type":"article","venue":"Climate Law","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Negotiation; Carbon capture and storage (timeline); Climate change mitigation; Climate change; State (computer science); International law; Clean Development Mechanism; Carbon fibers; Environmental planning; Environmental protection; Range (aeronautics); Environmental science; Business; Environmental resource management; Natural resource economics; Political science; Engineering; Computer science; Economics; Ecology; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001219167,0.0001739754,0.0002786894,0.0001322598,0.0002332247,0.0001377678,0.0001621802,0.0001520356,0.00009970645],"category_scores_gemma":[0.00003942201,0.0001754455,0.00005471989,0.0001605944,0.0001113849,0.0005287881,0.00009766215,0.0001958283,0.0002095548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001132025,"about_ca_system_score_gemma":0.000002765349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000342364,"about_ca_topic_score_gemma":0.0006978107,"domain_scores_codex":[0.9985777,0.00003315731,0.0004513221,0.0002744218,0.00002586193,0.0006375161],"domain_scores_gemma":[0.9992951,0.0001031186,0.0002452014,0.0002602274,0.00001026848,0.00008610935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001594173,0.00006311211,0.2717384,0.0001217541,0.00001216238,0.000002617947,0.007620726,0.00005928857,0.00002499341,0.7201784,0.0001455203,0.00001708421],"study_design_scores_gemma":[0.00321584,0.0001725032,0.8687738,0.0003185559,0.00007375111,0.0001067662,0.01092805,0.04625861,0.0004309753,0.02123714,0.04625241,0.002231636],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9489487,0.002142926,0.000003287524,0.0006895011,0.0003963312,0.0002415374,0.0003127769,0.00003084816,0.04723412],"genre_scores_gemma":[0.9968152,0.001792295,0.00006538244,0.0008326643,0.0002945628,0.00005017096,0.00006926982,0.00002764731,0.00005281656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6989412,"threshold_uncertainty_score":0.7154461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06813691738347309,"score_gpt":0.2570256561426488,"score_spread":0.1888887387591757,"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."}}