{"id":"W7034906635","doi":"","title":"When the Teeth Eat the Tail: A Review of Canada's Defence Artificial Intelligence","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Selenium in Biological Systems","field":"Nursing","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Artificial Sweetener; Applications of artificial intelligence; Key (lock); Subconscious","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004247928,0.0005911029,0.00080535,0.004607818,0.002309327,0.004458513,0.001770912,0.002403548,0.007128226],"category_scores_gemma":[0.008456519,0.0002713791,0.0004306172,0.007959186,0.004232602,0.002024906,0.001517334,0.002317705,0.001207358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02497193,"about_ca_system_score_gemma":0.04955048,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6527752,"about_ca_topic_score_gemma":0.8576978,"domain_scores_codex":[0.9984794,0.0002622044,0.0001192269,0.0001079191,0.0008323371,0.0001988254],"domain_scores_gemma":[0.9912935,0.003716982,0.0003141956,0.0001421088,0.004014788,0.0005184197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007191727,0.00003057621,0.0008148421,0.008937567,0.00004590029,0.0001433185,0.001850241,0.000299952,0.0002341052,0.02035518,0.217504,0.7497124],"study_design_scores_gemma":[0.000003033057,0.00001253047,0.001120635,0.005089686,0.0000188505,0.00007083239,0.0005765136,0.00002085237,0.00008768983,0.0008320208,0.9921544,0.00001308564],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0007262104,0.9629166,0.0002273963,0.02107799,0.001345177,0.00001005157,0.0000979499,0.00001703176,0.01358148],"genre_scores_gemma":[0.008120791,0.9742363,0.0006421612,0.008033502,0.0004609686,0.000009994375,0.00009222132,0.00002564665,0.008378397],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9976907,"threshold_uncertainty_score":0.6985393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1139811215087592,"score_gpt":0.3022676606162668,"score_spread":0.1882865391075075,"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."}}