{"id":"W2917961622","doi":"10.1145/3308774.3308785","title":"Report on CLEF 2018","year":2019,"lang":"en","type":"article","venue":"ACM SIGIR Forum","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Computer Research Institute of Montréal","funders":"","keywords":"Clef; Contextualization; Computer science; Ninth; Social media; Presentation (obstetrics); World Wide Web; Library science","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":[0.0004041814,0.00005506988,0.00007359766,0.00004272393,0.0001749188,0.00006533776,0.0002463943,0.00006506561,0.001905922],"category_scores_gemma":[0.0007935596,0.00004744116,0.00004176255,0.0001241606,0.00004053437,0.0003435826,0.0000441116,0.0000663841,0.005104347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005061542,"about_ca_system_score_gemma":0.00008989343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002150617,"about_ca_topic_score_gemma":0.00008894643,"domain_scores_codex":[0.9991295,0.0000216312,0.0001450104,0.00009488529,0.0003323153,0.0002766627],"domain_scores_gemma":[0.9993156,0.00006280666,0.00008211955,0.0003956705,0.00003394586,0.0001099142],"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":[0.0000243706,0.00004925088,0.01838651,0.000007309766,0.00001391796,0.00001282488,0.01235797,0.0000093658,0.00008980649,0.09584225,0.8395262,0.03368027],"study_design_scores_gemma":[0.0001564608,0.00006135646,0.01152911,0.000009746344,0.000001772668,0.000003347122,0.004096838,0.000008427607,0.0002257635,0.002613202,0.9812036,0.00009037078],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3958201,0.000006805827,0.00001135433,0.007449599,0.000664831,0.0001313432,0.000001659648,0.00006930081,0.595845],"genre_scores_gemma":[0.9426276,0.000014607,0.00009758379,0.003126262,0.00009630673,6.74191e-7,0.000005918407,0.000005002626,0.05402604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5468075,"threshold_uncertainty_score":0.9990065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02534437264239013,"score_gpt":0.3248668344821655,"score_spread":0.2995224618397754,"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."}}