{"id":"W4294549672","doi":"10.1146/annurev-environ-120920-100056","title":"Digitalization and the Anthropocene","year":2022,"lang":"en","type":"article","venue":"Annual Review of Environment and Resources","topic":"Innovation Diffusion and Forecasting","field":"Decision Sciences","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Anthropocene; Planetary boundaries; Sustainability; Politics; Natural resource economics; Unintended consequences; Equity (law); Environmental resource management; Corporate governance; Dematerialization (economics); Business; Economic system; Geography; Political science; Economics; Ecology","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":[0.001062554,0.0002483728,0.0002431123,0.00160067,0.001111228,0.003405602,0.0002511444,0.001091324,0.004437918],"category_scores_gemma":[0.002625561,0.0001179996,0.0001685864,0.001909939,0.00663755,0.005162179,0.002424073,0.001445601,0.0002723766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002046289,"about_ca_system_score_gemma":0.001084306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003873065,"about_ca_topic_score_gemma":0.004143736,"domain_scores_codex":[0.9995104,0.0002019236,0.00002484127,0.00009247291,0.00008388816,0.00008648761],"domain_scores_gemma":[0.998755,0.0007166798,0.0002141598,0.0001098772,0.00008266634,0.0001216493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002880294,0.00003673319,0.005218664,0.0003894258,0.00002648072,0.0002459567,0.003694247,0.001254305,0.0002632552,0.8108598,0.005783494,0.1721988],"study_design_scores_gemma":[0.000008409368,0.00004841584,0.01509108,0.001174953,0.0000166425,0.0004602469,0.004844705,0.0004951049,0.0002119692,0.3504517,0.6271742,0.00002261639],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.1278203,0.3741819,0.008278,0.08921669,0.0007105909,0.00005423838,0.0002978951,0.00006768299,0.3993728],"genre_scores_gemma":[0.7526882,0.233716,0.002061527,0.003229944,0.0008318592,0.00004685792,0.00009914886,0.00001640647,0.007310051],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004437918,"threshold_uncertainty_score":0.01484692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02841441088118458,"score_gpt":0.3047905890116118,"score_spread":0.2763761781304272,"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."}}