{"id":"W4405395529","doi":"10.1016/j.seppur.2024.131058","title":"Spontaneous supergravity field drives liquid-phase microelements to enhance CO2 capture through self revolution coupling","year":2024,"lang":"en","type":"article","venue":"Separation and Purification Technology","topic":"Spacecraft and Cryogenic Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; National University's Basic Research Foundation of China; Science and Technology Commission of Shanghai Municipality","keywords":"Supergravity; Coupling (piping); Field (mathematics); Phase (matter); Physics; Materials science; Metallurgy; Particle physics; Supersymmetry; Quantum mechanics; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005198552,0.0001702293,0.00009617814,0.0001039553,0.0001306193,0.0001905067,0.0002507118,0.0001812357,0.001602003],"category_scores_gemma":[0.00009047275,0.0001129669,0.00009417355,0.00009199144,0.0002745177,0.0002247041,0.0003488538,0.000192608,0.000285245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001731418,"about_ca_system_score_gemma":0.00009998235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001863014,"about_ca_topic_score_gemma":0.0006119463,"domain_scores_codex":[0.9999579,0.000004996028,0.000001482727,0.000009719926,0.00001474628,0.00001114374],"domain_scores_gemma":[0.999956,0.00001390686,0.00001116069,0.000005811854,0.000004922293,0.000008155655],"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":[0.00006073286,0.00001484175,0.0001667761,0.0000327613,0.000004079292,0.00004193336,0.00004605421,0.0004532516,0.9932753,0.003272988,0.0001794371,0.002451897],"study_design_scores_gemma":[0.00001782111,0.0001152377,0.0005702921,0.000002840751,0.000004117967,0.00004377448,0.00003950477,0.0114089,0.9843805,0.0004685256,0.002940394,0.000008007997],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9846804,0.0003269006,0.008428603,0.0001142364,0.00005768219,0.00001172539,0.0000344094,0.0001567085,0.006189446],"genre_scores_gemma":[0.9972054,0.00007383884,0.001420027,0.00003000696,0.000008416796,0.00000713742,0.00001728184,0.00001563879,0.001222197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001602003,"threshold_uncertainty_score":0.005359232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006826542426566941,"score_gpt":0.293068679266443,"score_spread":0.2862421368398761,"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."}}