{"id":"W6889234835","doi":"10.25545/zcxqmo","title":"Transforming Aluminium Waste: Sustainable Conversion to Commercial MOFs, Hydrogen Fuel, and Essential Aluminium Feedstocks","year":2025,"lang":"en","type":"dataset","venue":"UNB Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Aluminium; Raw material; Hydrogen; Hydrogen production; Production (economics)","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":[0.001421947,0.002250086,0.001149751,0.003676178,0.0008817049,0.002872841,0.002636675,0.003305646,0.03149761],"category_scores_gemma":[0.007529963,0.0006241397,0.002158594,0.006326191,0.000707895,0.001907077,0.002638786,0.002110913,0.02815397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002478896,"about_ca_system_score_gemma":0.003523907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06571082,"about_ca_topic_score_gemma":0.1001068,"domain_scores_codex":[0.9986985,0.0002240028,0.0001696502,0.0003036309,0.0004080621,0.0001961022],"domain_scores_gemma":[0.9979007,0.0006178521,0.0002462903,0.0004341276,0.000572159,0.0002288203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001390966,0.00003878533,0.001337255,0.002572321,0.00009939342,0.00003906299,0.00004874639,0.001453679,0.0003816798,0.002109042,0.9868356,0.004945401],"study_design_scores_gemma":[0.0002270139,0.00002039294,0.003949846,0.000839675,0.00007454871,0.00004949957,0.00013216,0.0007252546,0.0006576083,0.002702361,0.9905766,0.00004498901],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001857995,0.0002055781,0.00006175477,0.0001850481,0.00003429467,0.000008732451,0.9985455,0.0001475282,0.0006258229],"genre_scores_gemma":[0.0007409884,0.0002527344,0.0003885304,0.0001085725,0.000007333058,0.00005012707,0.9979377,0.00004156699,0.0004724461],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06571082,"threshold_uncertainty_score":0.1306567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008084488991214027,"score_gpt":0.2543938175672523,"score_spread":0.2463093285760382,"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."}}