{"id":"W7027211397","doi":"","title":"Captura and Deep Sky partner to fight climate change by deploying ocean carbon removal in Canada","year":2023,"lang":"en","type":"other","venue":"","topic":"Ocean Acidification Effects and Responses","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climate change; Carbon fibers; Global warming; Sky; Greenhouse gas; Global change; Climate system","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":[0.0004419616,0.0002360415,0.0001551383,0.0005726404,0.004797298,0.00238866,0.000822051,0.001244496,0.02418992],"category_scores_gemma":[0.001348263,0.0001372418,0.0002788433,0.0008463697,0.0007052291,0.000408295,0.001741913,0.001524664,0.002431977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02489785,"about_ca_system_score_gemma":0.1229314,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9922327,"about_ca_topic_score_gemma":0.9980527,"domain_scores_codex":[0.9993405,0.00002180959,0.000005446747,0.00003059178,0.0002331818,0.0003685071],"domain_scores_gemma":[0.9980459,0.00005639856,0.00002996182,0.00002850056,0.0007685966,0.001070613],"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":[0.0002012466,0.0001924602,0.0334592,0.0001601961,0.00004014681,0.0005244429,0.0009412529,0.001235965,0.001282014,0.008742191,0.8680905,0.08513035],"study_design_scores_gemma":[0.00006413925,0.00007263329,0.07103907,0.0001792672,0.00003282724,0.0001194206,0.006873209,0.001444042,0.001201603,0.001234777,0.9176965,0.00004239176],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1207774,0.003566408,0.001324072,0.07881459,0.002451658,0.0003582648,0.01609435,0.0009194601,0.7756937],"genre_scores_gemma":[0.2219639,0.002763981,0.001755291,0.01212742,0.0001479819,0.00007424638,0.004220164,0.000262158,0.7566848],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02489785,"threshold_uncertainty_score":0.1806474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01331306337179254,"score_gpt":0.2055315935923506,"score_spread":0.1922185302205581,"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."}}