{"id":"W4413813192","doi":"10.1016/j.nxmate.2025.101119","title":"Machine learning for data-driven insights into CO2 adsorption on amorphous porous organic polymers","year":2025,"lang":"en","type":"article","venue":"Next Materials","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation, Science and Economic Development Canada","funders":"Deanship of Scientific Research, University of Jordan; King Fahd University of Petroleum and Minerals","keywords":"Porosity; Adsorption; Polymer; Amorphous solid; Materials science; Organic polymer; Porous medium; Nanotechnology; Chemical engineering; Chemistry; Organic chemistry; Engineering; Composite material","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":[0.000682221,0.0004486525,0.0003391312,0.0004493122,0.0001460645,0.000502828,0.0003450153,0.0004348605,0.0005270623],"category_scores_gemma":[0.00198994,0.0001554152,0.0003906709,0.0003943366,0.0003300605,0.0005955285,0.0002358492,0.0007006607,0.0001139128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004653366,"about_ca_system_score_gemma":0.0005484123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001996155,"about_ca_topic_score_gemma":0.002537274,"domain_scores_codex":[0.9998565,0.00005491833,0.000005789856,0.0000283238,0.00004180501,0.00001254751],"domain_scores_gemma":[0.9994141,0.0004107942,0.00005892708,0.00003913298,0.00006289744,0.0000141368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006180396,0.0001306007,0.003689433,0.0001584951,0.00004406471,0.00007056914,0.0000231792,0.9288198,0.0140115,0.008371508,0.0007206728,0.0438983],"study_design_scores_gemma":[0.000001126142,0.000007304226,0.000263354,0.000001971409,0.000001511101,0.000002506574,0.000001830442,0.9966691,0.001187631,0.001711839,0.0001500796,0.000001668589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3772097,0.001611383,0.6159476,0.0008872245,0.00004957776,0.00005332407,0.0009787861,0.0008218392,0.002440637],"genre_scores_gemma":[0.9428712,0.0006884859,0.0551236,0.00006301537,0.00003066596,0.00005294942,0.0005517635,0.00002322078,0.0005950683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001996155,"threshold_uncertainty_score":0.003969073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0161920358917713,"score_gpt":0.2344941915618234,"score_spread":0.2183021556700521,"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."}}