{"id":"W6888447041","doi":"10.18738/t8/ejonhj/nefpdy","title":"IMGEO2_2018155_DEV_JKB2t_X97a.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":[0.001140868,0.003931854,0.002043901,0.00379999,0.001424839,0.004109527,0.004653065,0.003706091,0.2830231],"category_scores_gemma":[0.006157924,0.001267687,0.002008563,0.006485587,0.0007438801,0.00271176,0.003412899,0.002662256,0.4245023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001914577,"about_ca_system_score_gemma":0.002576584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03057746,"about_ca_topic_score_gemma":0.05361618,"domain_scores_codex":[0.9988909,0.0001814656,0.00008305582,0.0003729262,0.0002218758,0.0002498216],"domain_scores_gemma":[0.9977912,0.0006794393,0.000150695,0.0005502451,0.0005372404,0.0002911905],"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":[0.00002672824,0.000007198845,0.0001108042,0.0002046067,0.000008008673,0.00000634482,0.000008961064,0.00007960142,0.00003600655,0.0001639084,0.9988019,0.0005459152],"study_design_scores_gemma":[0.0002658964,0.0000182872,0.001255318,0.0002177755,0.00001924965,0.00003267189,0.00007129835,0.0003584592,0.0003101813,0.001200743,0.9962193,0.00003090708],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004205819,0.00003332927,0.00003742178,0.0000642469,0.00003442968,0.000005690351,0.9982494,0.0006768607,0.000856565],"genre_scores_gemma":[0.0001348575,0.00002988006,0.0001319842,0.00004944855,0.000009045755,0.00003864301,0.998395,0.0002434136,0.0009677393],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7169769,"threshold_uncertainty_score":0.9468064,"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."}}