{"id":"W2591784671","doi":"10.1002/cjce.22827","title":"Study on regenerative process of the new carbon capture technique based on antisolvent crystallization to strengthen crystallization","year":2017,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science and Technology Development Agency; National Natural Science Foundation of China","keywords":"Crystallization; Carbonization; Ammonia; Desorption; Chemical engineering; Carbon fibers; Materials science; Crystal (programming language); Activation energy; Process (computing); Mother liquor; Process engineering; Chemistry; Adsorption; Organic chemistry; Composite material; Computer science; Scanning electron microscope; Composite number","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0001627272,0.0002154267,0.0002927615,0.0002942875,0.0002247684,0.0002348107,0.0002283435,0.0002551132,0.0007257742],"category_scores_gemma":[0.0001556956,0.0001328524,0.0004339377,0.0002477071,0.0002651494,0.0004725349,0.0001419899,0.0004149993,0.000158342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002660179,"about_ca_system_score_gemma":0.0002732654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001088665,"about_ca_topic_score_gemma":0.001280394,"domain_scores_codex":[0.9998573,0.000007530591,0.000006685166,0.0000298625,0.00006949269,0.00002913043],"domain_scores_gemma":[0.9999344,0.0000152854,0.00001403692,0.000008035428,0.00002110019,0.000007058086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003616858,0.0000204197,0.0001282221,0.0001750226,0.000004498685,0.00006970533,0.00004173632,0.0002421511,0.9951862,0.0005145902,0.00004585342,0.003535545],"study_design_scores_gemma":[0.000004959255,0.000111619,0.0007088048,0.000005480555,0.000009333012,0.00009984431,0.00002106569,0.002183662,0.9954333,0.00004300156,0.001372038,0.000006764531],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795561,0.00386561,0.01218933,0.0001084225,0.00007162512,0.00005606276,0.00006896823,0.0001060673,0.003977829],"genre_scores_gemma":[0.9892848,0.001880639,0.00633358,0.000028401,0.00001964395,0.00002497604,0.00006093818,0.00002132727,0.002345631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001088665,"threshold_uncertainty_score":0.002427936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01176641445192183,"score_gpt":0.2162647684570791,"score_spread":0.2044983540051573,"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."}}