{"id":"W7006202183","doi":"","title":"TimeBites Episode 1: Origins of Canada's Navy","year":2015,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Plant Ecology and Taxonomy Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Navy; Prime minister; First world war; World War II; Government (linguistics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0007891072,0.0004148674,0.0004060878,0.001569207,0.02214086,0.009193794,0.001378973,0.003683475,0.03107056],"category_scores_gemma":[0.005070872,0.0003739894,0.0002594757,0.004022583,0.002865132,0.003163168,0.0053808,0.007627986,0.002673843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04247151,"about_ca_system_score_gemma":0.04964036,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9741825,"about_ca_topic_score_gemma":0.9881397,"domain_scores_codex":[0.9977314,0.0001126615,0.00004174772,0.0001383396,0.0009178965,0.001058012],"domain_scores_gemma":[0.9971615,0.0002922954,0.0001349306,0.00009299051,0.001137718,0.001180607],"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":[0.00008788415,0.00003376263,0.008906864,0.0001740086,0.00001629203,0.001826471,0.06765561,0.0001921797,0.0002929706,0.06032049,0.8310238,0.02946958],"study_design_scores_gemma":[0.000002619482,0.000003533989,0.005206132,0.0001611927,0.000003908342,0.0001462787,0.02553377,0.00002701671,0.0001219407,0.0006136795,0.9681609,0.00001900413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1140915,0.006853404,0.001370375,0.1076,0.006354711,0.0002079131,0.01429785,0.000291192,0.748933],"genre_scores_gemma":[0.4068525,0.006529944,0.000697008,0.03345325,0.0007663883,0.0001260907,0.005752343,0.0003963401,0.5454261],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04247151,"threshold_uncertainty_score":0.3081538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007507374225986669,"score_gpt":0.158768394274732,"score_spread":0.1512610200487453,"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."}}