{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00119116,0.0005987444,0.0008299433,0.00009269641,0.0002583579,0.0001515971,0.000749091,0.0003361328,0.00003449276],"category_scores_gemma":[0.0001082417,0.0003921309,0.002521712,0.0003972773,0.0001318356,0.0001850237,0.0001399707,0.0007803692,0.00005113893],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004041265,"about_ca_system_score_gemma":0.0004806448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006836931,"about_ca_topic_score_gemma":0.000009468166,"domain_scores_codex":[0.9967949,0.00006486155,0.0008867605,0.0002871302,0.001012231,0.0009540796],"domain_scores_gemma":[0.9976315,0.0003637297,0.0001765754,0.0007599479,0.0003732318,0.0006949535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005520233,0.001988243,0.002516044,0.001114046,0.01293713,0.0001151017,0.02095368,0.5499494,0.00847924,0.001202284,0.3842001,0.01599275],"study_design_scores_gemma":[0.04383454,0.01121096,0.004284809,0.002626936,0.00652643,0.001842705,0.01458107,0.229923,0.1073223,0.004232505,0.5702125,0.003402177],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9312643,0.02775931,0.01040628,0.01327545,0.007816233,0.003794138,0.0003748408,0.0003364087,0.004973011],"genre_scores_gemma":[0.9746631,0.002886984,0.01429809,0.0001335767,0.002996638,0.00008595819,0.0000153927,0.0003000965,0.004620116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3200264,"threshold_uncertainty_score":0.9998531,"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."}}