{"id":"W4239089772","doi":"10.18438/b8c89b","title":"Announcing ISHIMR 2015!","year":2014,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Library science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0008851304,0.00008978647,0.00007434463,0.0001286472,0.0002037359,0.001179214,0.0003298039,0.00005646015,0.00003635761],"category_scores_gemma":[0.001727981,0.0000834984,0.00002234437,0.000404977,0.00002090374,0.4176956,0.0001107265,0.0001645688,0.0001436713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007165504,"about_ca_system_score_gemma":0.00008488938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006161541,"about_ca_topic_score_gemma":1.590947e-8,"domain_scores_codex":[0.9990417,0.0002016079,0.0002366902,0.0001373539,0.000248939,0.0001336848],"domain_scores_gemma":[0.9979972,0.001316365,0.0002183139,0.0003223535,0.00005415621,0.00009163509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009589024,0.00002243199,0.0004450612,0.00008705293,0.000008052167,0.000001601112,0.0005419353,0.0005643456,0.0001271865,0.8344634,0.01949481,0.1441482],"study_design_scores_gemma":[0.0001608444,0.0001409993,0.003062338,0.00009717149,0.000005945482,0.0000266533,0.00004673337,0.1364091,0.001904704,0.0006371063,0.8573726,0.0001358115],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001116242,0.0002970714,0.8555914,0.126614,0.0005704741,0.0001336785,0.000001081913,0.0004435088,0.01523254],"genre_scores_gemma":[0.6766696,0.0005460361,0.1106652,0.2114846,0.0003523356,0.00002316573,0.00001628317,0.000009559915,0.0002333309],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8378778,"threshold_uncertainty_score":0.9998577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01067966088164853,"score_gpt":0.2334378828490037,"score_spread":0.2227582219673552,"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."}}