{"id":"W4410777258","doi":"10.1016/j.mseb.2025.118450","title":"Machine learning-driven optimization of physical properties in Al-Ga Co-doped ZnO films for hydrogen production applications","year":2025,"lang":"en","type":"article","venue":"Materials Science and Engineering B","topic":"ZnO doping and properties","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Deanship of Scientific Research, University of Jordan; Jordan University of Science and Technology","keywords":"Materials science; Doping; Hydrogen production; Hydrogen; Production (economics); Nanotechnology; Chemical engineering; Computer science; Optoelectronics; Chemistry; Engineering","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":[0.0001073675,0.0001468894,0.0001359505,0.00007549423,0.00009602481,0.0002194923,0.0001850801,0.0001936458,0.000582755],"category_scores_gemma":[0.0003034567,0.0001127225,0.0001338511,0.0001054851,0.00008817889,0.0001383698,0.0000772429,0.0001775905,0.00005670483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000343929,"about_ca_system_score_gemma":0.0001909069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00228763,"about_ca_topic_score_gemma":0.004457429,"domain_scores_codex":[0.9999777,0.000003462651,7.095143e-7,0.000005690116,0.000007266549,0.000005147892],"domain_scores_gemma":[0.9999141,0.00004770966,0.00001459674,0.000003456551,0.00001490554,0.000005363064],"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":[0.0002125266,0.0001110666,0.002436508,0.00008081068,0.00002880113,0.00008348624,0.0000207371,0.7890026,0.1874687,0.001036596,0.0003986143,0.01911948],"study_design_scores_gemma":[0.000008363661,0.00003425924,0.0004977379,0.000001130678,0.000003626485,0.000004906489,0.000004303791,0.9855748,0.01364883,0.0001067222,0.0001136451,0.000001567393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689849,0.0003146353,0.02664355,0.0001570974,0.00002719948,0.00001496914,0.00006453783,0.00009528863,0.003697842],"genre_scores_gemma":[0.9953968,0.00003754078,0.004099157,0.000009140812,0.000002593384,0.000004888787,0.00002164459,0.00001094881,0.00041724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00228763,"threshold_uncertainty_score":0.004548609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01385043231162495,"score_gpt":0.2368538305410843,"score_spread":0.2230033982294593,"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."}}