{"id":"W3139071358","doi":"10.5555/3041021.3252705","title":"Session details: AMCH'17 Session 1: Technology","year":2017,"lang":"en","type":"article","venue":"The Web Conference","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Session (web analytics); Computer science; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.005709412,0.001893178,0.002214374,0.002264915,0.005741598,0.01383357,0.002125208,0.006278447,0.7415943],"category_scores_gemma":[0.006321406,0.0006278196,0.002017505,0.002197701,0.0008208511,0.004800251,0.008929144,0.005174501,0.5475553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002697745,"about_ca_system_score_gemma":0.004879588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003305927,"about_ca_topic_score_gemma":0.009200512,"domain_scores_codex":[0.9974068,0.0004545394,0.00007609072,0.0003712945,0.0009187427,0.0007725305],"domain_scores_gemma":[0.9918601,0.0007545108,0.0002469544,0.0007248312,0.002299887,0.004113757],"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":[0.00009867975,0.00003531373,0.00009656396,0.00009735678,0.000007005497,0.00001585557,0.00003067799,0.00004011428,0.0001810664,0.000763259,0.9894975,0.0091365],"study_design_scores_gemma":[0.00004221648,0.00006031628,0.0009662918,0.0001206528,0.000009349691,0.00001684963,0.0001177906,0.0001290454,0.000240025,0.001173528,0.9971076,0.00001642959],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003171464,0.007714272,0.005471302,0.0391463,0.1624935,0.001978583,0.02687892,0.005481266,0.7476644],"genre_scores_gemma":[0.009866722,0.002150356,0.001318537,0.003569716,0.02122757,0.001308237,0.009140469,0.002059237,0.9493592],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2584057,"threshold_uncertainty_score":0.3685844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08207694747843085,"score_gpt":0.2507165536943053,"score_spread":0.1686396062158744,"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."}}