{"id":"W4392898938","doi":"10.61838/kman.aitech.1.3.1","title":"Sustainability and AI: Prioritizing Environmental Considerations in Tech Advancements","year":2023,"lang":"en","type":"article","venue":"","topic":"Green IT and Sustainability","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Sustainability; Environmental stewardship; Transformative learning; Stewardship (theology); Software deployment; Harmony (color); Sustainable development; Business; Environmental resource management; Engineering; Political science; Sociology; Economics; Politics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001525689,0.00007897851,0.00008815526,0.00008333938,0.00005615442,0.00002167057,0.00002352809,0.00003729486,0.00006342278],"category_scores_gemma":[0.00007083907,0.00008498343,0.00001213237,0.0001466591,0.00004676839,0.0001598462,0.00004384049,0.00009701942,0.00001046924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002285569,"about_ca_system_score_gemma":0.00001846249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003057567,"about_ca_topic_score_gemma":0.000059884,"domain_scores_codex":[0.9994197,0.00001451855,0.0001472638,0.0001394901,0.0000599315,0.0002191071],"domain_scores_gemma":[0.9997716,0.00005618423,0.00000432104,0.0001248299,0.00001051881,0.0000325387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004429171,0.00006376609,0.9647408,0.0003252631,0.00001577944,0.00006086844,0.001268976,0.006977276,0.004070589,0.004644448,0.0007237358,0.01710413],"study_design_scores_gemma":[0.000810349,0.00003270411,0.8985469,0.00001014971,0.000005945526,0.000007666909,0.008087482,0.02454072,0.0009988009,0.06192119,0.004706684,0.0003314522],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977355,0.0001016894,0.0004269679,0.0003818441,0.00004796423,0.0003058909,0.000005075457,0.0002526948,0.0007423956],"genre_scores_gemma":[0.9994424,0.00001740815,0.0002531559,0.0000261607,0.000005843733,0.00003620992,0.000007723859,0.000009052651,0.0002020545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06619387,"threshold_uncertainty_score":0.3465524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005284593373932596,"score_gpt":0.2272712787660299,"score_spread":0.2219866853920973,"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."}}