{"id":"W4241027835","doi":"10.1016/b978-0-12-815503-5.00008-5","title":"The Future","year":2019,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Artificial Intelligence Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Context (archaeology); Section (typography); Set (abstract data type); Realization (probability); Artificial intelligence; Data science; Focus (optics); Engineering; Geography; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006758941,0.0005127049,0.0003793773,0.0006503193,0.001814576,0.00578714,0.0006592756,0.002002214,0.2110643],"category_scores_gemma":[0.001140733,0.0001868706,0.0003104568,0.001066285,0.001953698,0.005350194,0.002817874,0.002754286,0.08074779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002062907,"about_ca_system_score_gemma":0.003234802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003834452,"about_ca_topic_score_gemma":0.007809247,"domain_scores_codex":[0.9995614,0.00009549766,0.00001069341,0.00008089012,0.0001624833,0.00008892893],"domain_scores_gemma":[0.9996287,0.00005738697,0.00002006255,0.00005248326,0.0000977209,0.0001436647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002017562,0.00002146142,0.0001146066,0.0001254396,0.000003219663,0.00004785862,0.0005181855,0.00006709385,0.0002376736,0.2090018,0.6207014,0.1691411],"study_design_scores_gemma":[9.741327e-7,0.000002167698,0.00006261651,0.00005953931,6.03611e-7,0.00001786423,0.0001325497,0.00000900044,0.00001136537,0.007966185,0.991736,0.000001138473],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005425277,0.02522149,0.0007958709,0.01977651,0.005458386,0.00001162325,0.000112903,0.00007398229,0.9480067],"genre_scores_gemma":[0.007581349,0.01478563,0.0006292599,0.00481729,0.001422066,0.0000245716,0.0001323167,0.00006158971,0.9705461],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7889357,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01749477001969851,"score_gpt":0.2538748465858255,"score_spread":0.236380076566127,"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."}}