{"id":"W6931688004","doi":"10.5683/sp3/iku4hc","title":"Coronation Alberta. 1:50,000. Map Sheet 073D03, ed. 1, 1969","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Georeference; Coronation; General partnership; Raster graphics; Natural (archaeology); Government (linguistics); Aerial photography; Topographic map (neuroanatomy)","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":[0.000525785,0.001922392,0.001363065,0.005085241,0.001183706,0.003434146,0.002005514,0.0006490793,0.1280368],"category_scores_gemma":[0.002575159,0.0007917273,0.0006417928,0.02119694,0.0004753687,0.0009147671,0.0009509461,0.001199923,0.1270069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005705683,"about_ca_system_score_gemma":0.01216027,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8034226,"about_ca_topic_score_gemma":0.8730754,"domain_scores_codex":[0.9994235,0.00002788077,0.00003572618,0.0001381617,0.0002511271,0.0001235909],"domain_scores_gemma":[0.9983822,0.0001516448,0.0001126247,0.0002018669,0.0009555704,0.0001961336],"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":[0.00002149225,0.000003861068,0.0005835472,0.0002052788,0.00000910678,0.00001209213,0.00002185718,0.0001088068,0.00004213254,0.0002359576,0.995933,0.002822869],"study_design_scores_gemma":[0.0000504949,0.000003419327,0.009137545,0.0001681472,0.00001225662,0.00002420121,0.00009924311,0.000112527,0.0001235151,0.0004281678,0.9898216,0.00001899064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006292971,0.00007195502,0.00002681196,0.00002054416,0.00001358159,0.000003745774,0.9977828,0.0001569276,0.001860816],"genre_scores_gemma":[0.0003462216,0.0001175488,0.0001848694,0.00001807903,0.000004930071,0.00001607659,0.9956175,0.00009401823,0.003600815],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1965774,"threshold_uncertainty_score":0.4283257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007501865161262026,"score_gpt":0.244014860387424,"score_spread":0.236512995226162,"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."}}