{"id":"W3207269482","doi":"","title":"기술자료 : 특허정보를 활용한 습식 이산화탄소 포집 기술동향 분석","year":2015,"lang":"ko","type":"article","venue":"Journal of the Korean Society for Heat Treatment","topic":"Engineering Applied Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Greenhouse gas; China; Carbon capture and storage (timeline); Patent analysis; Business; Natural resource economics; Political science; Climate change; Data science; Computer science; Economics","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":[0.001287559,0.0002818091,0.0001946024,0.002400081,0.0007139181,0.003048939,0.0003675396,0.0003766743,0.02241429],"category_scores_gemma":[0.003150225,0.00008254524,0.0002058225,0.004204941,0.0004735879,0.002146343,0.0004680871,0.0003626171,0.008326819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001607057,"about_ca_system_score_gemma":0.002079763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00398009,"about_ca_topic_score_gemma":0.0046902,"domain_scores_codex":[0.999154,0.00008247096,0.00007006486,0.0001519905,0.0004337718,0.0001077498],"domain_scores_gemma":[0.9978816,0.0003864513,0.000505537,0.00006663063,0.001056021,0.0001038127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003210262,0.000151811,0.08683717,0.001122373,0.00009074686,0.000881941,0.00126857,0.001176638,0.008147882,0.03838569,0.04601153,0.8156046],"study_design_scores_gemma":[0.00002329364,0.0003598216,0.1951245,0.0004426961,0.0001571004,0.00187549,0.003855017,0.003056978,0.01824297,0.01110135,0.7656633,0.00009744378],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5290133,0.02250097,0.01643325,0.01674582,0.001979629,0.0003926566,0.01190554,0.0003437731,0.4006851],"genre_scores_gemma":[0.8493026,0.01244173,0.007888425,0.000949015,0.0005038964,0.0001181274,0.003939361,0.00004330843,0.1248134],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02241429,"threshold_uncertainty_score":0.0749833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03795034231636155,"score_gpt":0.2814773149647093,"score_spread":0.2435269726483478,"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."}}