{"id":"W6908312058","doi":"10.25545/6dgf1v/ihbggo","title":"4_VLP.txt","year":2024,"lang":"en","type":"dataset","venue":"UNB Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Frame (networking); Identification (biology); Face (sociological concept); Intersection (aeronautics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000450719,0.0006898782,0.0005598512,0.0007460177,0.00009178976,0.0002905667,0.00173963,0.0005439479,0.1070208],"category_scores_gemma":[0.0003533279,0.0006628225,0.0002139637,0.0006965442,0.0001997163,0.000325998,0.001557282,0.001315992,0.9926747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003362806,"about_ca_system_score_gemma":0.0003262825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005179961,"about_ca_topic_score_gemma":0.0008630941,"domain_scores_codex":[0.9967661,0.0001100858,0.0004652089,0.001168406,0.0008172289,0.0006729545],"domain_scores_gemma":[0.995652,0.000095795,0.0001988799,0.003710658,0.00006415601,0.0002785248],"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":[0.00002865796,0.00008921998,6.472712e-7,0.0004074621,0.0002228205,0.001488618,0.00001354958,0.000001966623,0.0000133191,0.00004448117,0.9976076,0.00008158304],"study_design_scores_gemma":[0.0003009525,0.00003933082,9.625724e-7,0.0002992428,0.0007295231,0.00007119022,0.00004918527,0.00002033106,0.00001272506,0.0001004324,0.9976637,0.0007123607],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002273683,0.00003527805,5.753936e-7,0.00001050635,0.002830572,0.0003775667,0.9948501,0.0004258791,0.001467257],"genre_scores_gemma":[5.484814e-7,0.0002011285,0.0001074114,0.0002949327,0.00102782,0.00003390334,0.9956667,0.000215748,0.002451791],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.885654,"threshold_uncertainty_score":0.9995823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0200427862775651,"score_gpt":0.282335544886134,"score_spread":0.2622927586085689,"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."}}