{"id":"W6958397227","doi":"10.6084/m9.figshare.13003097","title":"Supplementary Material.pdf","year":2020,"lang":"en","type":"other","venue":"Figshare","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Process (computing); Natural (archaeology); Identification (biology)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00001309683,0.0001731787,0.0002064618,0.0001112818,0.00002789259,0.0002011449,0.0008532857,0.00008778582,0.9832875],"category_scores_gemma":[0.00001551557,0.0001658442,0.0001027716,0.0001766382,0.000001570664,0.00004924847,0.0004584294,0.0000741763,0.02371526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001215045,"about_ca_system_score_gemma":0.00002984573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002573837,"about_ca_topic_score_gemma":0.00001244232,"domain_scores_codex":[0.9990754,0.00002234603,0.0001399553,0.000373829,0.0002178782,0.0001705777],"domain_scores_gemma":[0.9993888,0.00001180288,0.0001423848,0.0003706631,0.000008728022,0.00007757803],"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":[2.196483e-7,0.000004491855,0.000002037009,0.00004463452,0.00003833108,0.00001821226,0.00001676524,1.3157e-7,0.000003756623,0.00003517384,0.998757,0.00107927],"study_design_scores_gemma":[0.00006889449,0.00001172763,0.000006645604,0.0005209709,0.000007221548,0.00000107916,0.000003892342,0.0003576166,0.0002279071,0.000006607551,0.9985988,0.0001886945],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[4.039968e-8,0.0001311559,0.00007963655,0.0004326341,0.0003714699,0.0001640749,0.496207,0.0002431045,0.5023709],"genre_scores_gemma":[0.000005654465,0.000007306156,0.004960048,0.001041059,0.0008588548,0.00005168055,0.6434544,0.0001297404,0.3494913],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.9595723,"threshold_uncertainty_score":0.9770449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03190010625448755,"score_gpt":0.2594325945120813,"score_spread":0.2275324882575938,"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."}}