{"id":"W3214388654","doi":"10.21203/rs.3.rs-1025154/v1","title":"Temporary Nature-based Carbon Removal Can Lower Peak Warming in a Well-below 2°C Scenario","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; Concordia University","funders":"","keywords":"Carbon fibers; Warming up; Environmental science; Global warming; Climate change; Natural resource economics; Economics; Computer science; Geology; Oceanography; Algorithm","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001490584,0.0005166033,0.0005299699,0.00008009899,0.0002220581,0.0001670364,0.001000392,0.001035218,0.001864388],"category_scores_gemma":[0.0001433034,0.0005268191,0.0002406021,0.0008101617,0.0006593473,0.0001090754,0.003545421,0.005116028,0.00007388386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003538317,"about_ca_system_score_gemma":0.0003878775,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01693001,"about_ca_topic_score_gemma":0.004076757,"domain_scores_codex":[0.9938353,0.0006368764,0.0005018646,0.001535422,0.002239875,0.001250679],"domain_scores_gemma":[0.9979634,0.0001608915,0.0001309694,0.001323126,0.00002378921,0.0003978399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002343563,0.001010045,0.5632303,0.0005708134,0.00004742324,0.006781668,0.001003683,0.4202949,0.001470059,0.00001313127,0.0006653595,0.004678321],"study_design_scores_gemma":[0.002453231,0.0005390181,0.4481673,0.003203116,0.00004853754,0.0000953659,0.003897991,0.5132437,0.0009566803,0.0008041244,0.02374011,0.002850835],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831291,0.00110935,0.0001005992,0.001025008,0.0003818773,0.0009837983,0.000011839,0.00006825275,0.01319019],"genre_scores_gemma":[0.9924892,0.0002542789,0.003921727,0.0003027667,0.0001230667,0.0001329031,0.0001638965,0.0001101699,0.002502005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.115063,"threshold_uncertainty_score":0.9997183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01658161079405683,"score_gpt":0.2908765107684415,"score_spread":0.2742948999743846,"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."}}