{"id":"W6888423200","doi":"10.18738/t8/ejonhj/lgidbo","title":"IMGEO2_2018157_DEV_JKB2t_X45a.txt","year":2024,"lang":"en","type":"dataset","venue":"Texas Digital Library (University of Texas)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001108311,0.003770142,0.001944605,0.003710745,0.001366624,0.00403343,0.004398152,0.00356883,0.2873676],"category_scores_gemma":[0.006106677,0.001218786,0.001895089,0.006375394,0.0007099718,0.002692204,0.003397973,0.002579958,0.4287394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001870884,"about_ca_system_score_gemma":0.002473827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02912389,"about_ca_topic_score_gemma":0.05152901,"domain_scores_codex":[0.9989259,0.00017321,0.00008103051,0.0003577988,0.0002152728,0.0002468866],"domain_scores_gemma":[0.9977544,0.000673329,0.0001510435,0.0005623975,0.0005558141,0.0003030232],"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":[0.0000255049,0.000007018827,0.0001109399,0.0001945919,0.000007145394,0.000005870397,0.000008883246,0.00007221866,0.00003445709,0.0001636985,0.9988137,0.0005557899],"study_design_scores_gemma":[0.0002453074,0.00001750598,0.001201927,0.0002089916,0.00001680221,0.00002943508,0.00007042177,0.0003227818,0.0002914109,0.001131615,0.9964353,0.00002845989],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004222158,0.0000320995,0.00003734059,0.00006827053,0.00003549715,0.000005893469,0.9981585,0.0006856828,0.000934447],"genre_scores_gemma":[0.0001370704,0.00003025256,0.0001344714,0.00005275843,0.00000956542,0.00003906304,0.9982932,0.0002487979,0.001054871],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7126324,"threshold_uncertainty_score":0.9613404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01060996403661756,"score_gpt":0.1914588396809049,"score_spread":0.1808488756442874,"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."}}