{"id":"W6968514805","doi":"10.5281/zenodo.3249347","title":"Interacting with Musebots (that don t really listen)","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"AI in Service Interactions","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Set (abstract data type); Perspective (graphical); Identification (biology); Focus (optics); Work (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000398576,0.0001490739,0.0001336063,0.0002233976,0.0009978553,0.001491534,0.002090566,0.00004753631,0.004959953],"category_scores_gemma":[0.0001800658,0.0001406875,0.00004299647,0.0005991352,0.00004840738,0.001499557,0.001770319,0.0003694761,0.01376918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001658598,"about_ca_system_score_gemma":0.000005580172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005688988,"about_ca_topic_score_gemma":0.000002323691,"domain_scores_codex":[0.998263,0.0002109559,0.0002017736,0.0005292743,0.000433069,0.0003619143],"domain_scores_gemma":[0.9981575,0.00008267414,0.0001610271,0.0009070914,0.0005436722,0.0001480606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005040883,0.001053173,0.0004888808,0.0004882858,0.0004169756,0.0002836728,0.02887625,0.002661962,0.0353766,0.08275484,0.2545344,0.5925609],"study_design_scores_gemma":[0.0004155575,0.0003510714,0.0009279295,0.0001226179,0.000006868007,0.0004454576,0.0007637511,0.006895871,0.000763567,0.00009124548,0.9889739,0.0002422322],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1808571,0.00002743205,0.1191776,0.004596491,0.001022012,0.001029035,0.00003497881,0.003590515,0.6896648],"genre_scores_gemma":[0.9917975,0.00001172829,0.004666049,0.000409932,0.00008610029,4.580967e-8,0.0001366358,0.0007161714,0.002175822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8109404,"threshold_uncertainty_score":0.999545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02951816595620755,"score_gpt":0.2440815847150704,"score_spread":0.2145634187588629,"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."}}