{"id":"W7010537715","doi":"","title":"Informationsarbetet i Norden 2018-2019","year":2019,"lang":"sv","type":"article","venue":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","topic":"Library Science and Administration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ridiculous; Government (linguistics); Quarter (Canadian coin)","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":[0.00349504,0.0006172374,0.00117784,0.007217133,0.001567457,0.009761021,0.0009728373,0.001304499,0.0543339],"category_scores_gemma":[0.009745625,0.0005841915,0.0007569253,0.01242223,0.0004907792,0.002901937,0.00415387,0.002178292,0.05194612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005564553,"about_ca_system_score_gemma":0.01789472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1106115,"about_ca_topic_score_gemma":0.1293589,"domain_scores_codex":[0.9962339,0.0002741554,0.0006441182,0.0004513942,0.001892651,0.0005037608],"domain_scores_gemma":[0.9943551,0.000801981,0.0007499699,0.0003266498,0.002801307,0.000965072],"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":[0.0008561392,0.00006207745,0.00478168,0.002854308,0.00006095304,0.0004099574,0.001156439,0.0003082342,0.0004517982,0.006721455,0.9116794,0.07065744],"study_design_scores_gemma":[0.00002015336,0.00001499679,0.004939566,0.0007474173,0.00001378124,0.00004195085,0.000538231,0.00002656286,0.0002484312,0.000361616,0.993035,0.00001233639],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.01566643,0.01936867,0.0007823041,0.006118638,0.005824764,0.0001871486,0.8128554,0.0009026404,0.1382939],"genre_scores_gemma":[0.03235942,0.01736681,0.002769105,0.001197164,0.0007274354,0.000349741,0.6745526,0.0009032403,0.2697745],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1106115,"threshold_uncertainty_score":0.2199355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02180582602686204,"score_gpt":0.283764764248338,"score_spread":0.261958938221476,"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."}}