{"id":"W7088163658","doi":"10.5281/zenodo.17317552","title":"Enhancing Carbon Capture And CO2 Reduction Processes Using Machine Learning And AI Technologies To Improve Biomedical Outcomes","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Greenhouse gas; Air quality index; Psychological intervention; Quality (philosophy); Health care; Emerging technologies","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":[0.0008639251,0.0008067176,0.000386068,0.001210589,0.0003751806,0.001474848,0.0007791389,0.0009589832,0.007544816],"category_scores_gemma":[0.001414772,0.000151414,0.0004478605,0.001229158,0.000436329,0.001261798,0.0007555935,0.0008244205,0.001990296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001254842,"about_ca_system_score_gemma":0.00102193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002662671,"about_ca_topic_score_gemma":0.003439303,"domain_scores_codex":[0.9995177,0.00007218408,0.00001761395,0.0001130761,0.000227677,0.00005173879],"domain_scores_gemma":[0.9993753,0.0002633033,0.00008546217,0.00007044449,0.0001645517,0.00004103638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006339328,0.001162811,0.005632055,0.001763487,0.0001758054,0.0003367277,0.0001039417,0.09908674,0.2613565,0.03716924,0.01742005,0.5751587],"study_design_scores_gemma":[0.0001490486,0.0007253317,0.005139207,0.0002162481,0.0001310716,0.0002555077,0.0001049554,0.3666363,0.5069723,0.0372985,0.08224668,0.0001248527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1588299,0.01915314,0.6719196,0.007171141,0.001337329,0.0006349459,0.002416189,0.005483247,0.1330545],"genre_scores_gemma":[0.8020379,0.009106785,0.1523961,0.0009430665,0.0002707808,0.0003547452,0.001266208,0.0004859377,0.03313854],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007544816,"threshold_uncertainty_score":0.02523994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008986425122076182,"score_gpt":0.2264790700055766,"score_spread":0.2174926448835004,"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."}}