{"id":"W6944423164","doi":"10.18738/t8/ejonhj/uhnxlb","title":"IMGEO2_2018155_DEV_JKB2t_X86a.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":[0.001137412,0.004057568,0.002039936,0.003740374,0.00139474,0.004023145,0.004634779,0.003681847,0.2724827],"category_scores_gemma":[0.005983909,0.001247423,0.002053002,0.006261447,0.0007532376,0.00269226,0.003434962,0.002665286,0.422971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001889065,"about_ca_system_score_gemma":0.002535572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02941723,"about_ca_topic_score_gemma":0.05197465,"domain_scores_codex":[0.9988708,0.0001821743,0.000083938,0.0003813676,0.000226319,0.0002553655],"domain_scores_gemma":[0.9978541,0.0006330662,0.0001446363,0.0005515387,0.0005256067,0.0002909621],"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":[0.00002734869,0.000007676581,0.000106961,0.000199165,0.00000795547,0.00000620346,0.000008548822,0.00007865625,0.00003802519,0.0001556861,0.9987923,0.000571438],"study_design_scores_gemma":[0.0002723416,0.00002004603,0.001254962,0.0002136552,0.00001950875,0.00003414644,0.00007200536,0.0003899849,0.000343945,0.001194272,0.9961535,0.00003166758],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004732809,0.0000358557,0.00004097909,0.00006844672,0.00003893399,0.00000647404,0.9980944,0.0007680107,0.0008996436],"genre_scores_gemma":[0.0001396872,0.00003029112,0.000138622,0.00005061476,0.000009543875,0.00003978674,0.9983453,0.0002484178,0.0009977524],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7275173,"threshold_uncertainty_score":0.9115454,"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."}}