{"id":"W4388732810","doi":"10.33137/ijidi.v7i3/4.41458","title":"Book Review: Boosting the Knowledge Economy: Key Contributions from Information Services in Educational, Cultural and Corporate Environments by Francisco-Javier Calzada-Prado (2022)","year":2023,"lang":"en","type":"article","venue":"The International Journal of Information Diversity & Inclusion (IJIDI)","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Boosting (machine learning); Key (lock); Knowledge management; Business; Computer science; Artificial intelligence; Computer security","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":[0.0014489,0.001262504,0.001872424,0.003249512,0.001042729,0.004668578,0.001133062,0.003591007,0.02543107],"category_scores_gemma":[0.004749052,0.0004459681,0.0005881489,0.005522541,0.001040526,0.004253191,0.001546014,0.004378209,0.01456123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002366087,"about_ca_system_score_gemma":0.003984141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008579493,"about_ca_topic_score_gemma":0.02533753,"domain_scores_codex":[0.9987094,0.0002219993,0.00008193711,0.0001778603,0.0007061949,0.0001025711],"domain_scores_gemma":[0.9956887,0.001690624,0.0002610741,0.00007160153,0.001746019,0.0005418606],"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":[0.000008011512,0.000007954498,0.00003513798,0.0004438864,0.000005835747,0.00001488688,0.00002605288,0.00002528571,0.00003304833,0.0006505971,0.9666778,0.03207143],"study_design_scores_gemma":[0.0000077326,0.00001336618,0.0002315446,0.0009510994,0.00001057244,0.00009526345,0.00004669229,0.00002642567,0.00004071937,0.0005783519,0.9979899,0.000008416528],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001365046,0.8185543,0.0003634143,0.07163625,0.09359205,0.00002844625,0.0001577176,0.00005428422,0.01547709],"genre_scores_gemma":[0.001927247,0.7429699,0.0008047063,0.05356024,0.08143686,0.00007296549,0.0003046787,0.0001251039,0.1187984],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02543107,"threshold_uncertainty_score":0.08507538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009896814183151172,"score_gpt":0.2225969869439319,"score_spread":0.2127001727607807,"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."}}