{"id":"W6931359986","doi":"10.5281/zenodo.6158756","title":"TopiOCQA DPR Retriever passage embeddings (original (2))","year":2022,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Media Forensic Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Object (grammar); Set (abstract data type); Labrador Retriever; Sequence (biology); Representation (politics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000510139,0.0002656036,0.0002412457,0.0005933819,0.0009842019,0.00148962,0.002816473,0.0001386901,0.08065356],"category_scores_gemma":[0.0004397437,0.0002959408,0.00009425969,0.001105271,0.0001412806,0.000418847,0.003296156,0.0005604499,0.01575897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003564883,"about_ca_system_score_gemma":0.000009565843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002553888,"about_ca_topic_score_gemma":5.381419e-7,"domain_scores_codex":[0.997336,0.0002372431,0.0002530433,0.0008076821,0.0008793223,0.000486758],"domain_scores_gemma":[0.9982835,0.00002339471,0.0002312346,0.001065439,0.0001754097,0.0002209961],"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":[0.000008034959,0.00004530765,3.650503e-7,0.00003805568,0.00003299301,0.00004486795,0.0002011767,0.000002122365,0.00003326883,0.01505445,0.8484521,0.1360873],"study_design_scores_gemma":[0.0002834369,0.0002295852,0.00001226091,0.00003735979,0.000009650726,0.0001637029,0.0000422155,0.0001839884,0.00005698793,0.0005586784,0.9981094,0.0003127365],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00002629727,0.00009491267,0.01729041,0.0004585737,0.0009630131,0.0004444117,0.0001664644,0.003329064,0.9772269],"genre_scores_gemma":[0.003641225,0.0001504265,0.004182198,0.0005478581,0.001017793,2.929982e-7,0.002238235,0.01190303,0.976319],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1496573,"threshold_uncertainty_score":0.9999493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01817167929091672,"score_gpt":0.2253179400616974,"score_spread":0.2071462607707807,"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."}}