{"id":"W3035416938","doi":"10.17632/xps2rnk8zp.1","title":"BarkNet 1.0 (Part 2 of 4)","year":2019,"lang":"en","type":"article","venue":"Mendeley Data","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Geology","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":[0.0008961018,0.004164118,0.001310711,0.002694866,0.0008570722,0.002188972,0.003890855,0.001989545,0.09151661],"category_scores_gemma":[0.003305134,0.001727288,0.001321453,0.002161204,0.0004351813,0.002996167,0.001706051,0.002355354,0.07678253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002213922,"about_ca_system_score_gemma":0.001891023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02094716,"about_ca_topic_score_gemma":0.03381673,"domain_scores_codex":[0.9993845,0.0000493169,0.00003682473,0.0002115364,0.0001828845,0.0001348729],"domain_scores_gemma":[0.9993522,0.0001114107,0.00003052523,0.0001903848,0.0002293483,0.00008623781],"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":[0.0004950523,0.0002125077,0.001098812,0.0006048315,0.0001272722,0.00009977107,0.0000503989,0.005992305,0.003892953,0.001099219,0.9156454,0.07068145],"study_design_scores_gemma":[0.001182839,0.0007669167,0.007904086,0.0004208409,0.0002385713,0.0005456283,0.0002409783,0.2023063,0.04881398,0.01323877,0.7241024,0.0002385509],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"dataset","genre_scores_codex":[0.0249303,0.002231924,0.02573669,0.0008900369,0.001761596,0.0008587437,0.3847632,0.5246055,0.03422205],"genre_scores_gemma":[0.05212802,0.001020395,0.06643072,0.0008136987,0.0002553552,0.001383517,0.829052,0.01826061,0.03065572],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.09151661,"threshold_uncertainty_score":0.3061536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04921821638335157,"score_gpt":0.3066972246073242,"score_spread":0.2574790082239727,"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."}}