{"id":"W1976969478","doi":"10.1016/j.procs.2014.07.002","title":"FNC 2014 Preface","year":2014,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Data 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":[],"consensus_categories":[],"category_scores_codex":[0.0006622779,0.0001131746,0.00009518766,0.0001486633,0.0001995848,0.0003927707,0.00189695,0.00002241388,0.000003662566],"category_scores_gemma":[0.0000722448,0.0001036416,0.00002692033,0.000703405,0.0001049065,0.0008625194,0.0004810816,0.00009450417,0.0001862675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004064282,"about_ca_system_score_gemma":0.0001995174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003327158,"about_ca_topic_score_gemma":4.955731e-7,"domain_scores_codex":[0.9985088,0.000009755423,0.0001434549,0.0004996731,0.000458237,0.0003801577],"domain_scores_gemma":[0.9989879,0.00008038701,0.00004438412,0.0005051321,0.0001831276,0.0001991359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[6.410809e-7,0.00007682169,0.001772149,0.00004167648,0.000004476763,0.000001193847,0.001200102,0.0445375,0.002090612,0.8373964,0.004798427,0.10808],"study_design_scores_gemma":[0.00006481679,0.00004097599,0.00902943,0.00001275104,8.72678e-7,0.00001603464,0.000001145617,0.9781166,0.001116706,0.005298254,0.006135247,0.0001671823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005568444,0.00003625729,0.9893458,0.001254565,0.001582373,0.00006631154,1.175349e-7,0.0002016597,0.001944408],"genre_scores_gemma":[0.5650842,0.000003766479,0.4342085,0.0003989226,0.000245176,0.000006490517,2.288112e-7,0.000004199739,0.00004855589],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9335791,"threshold_uncertainty_score":0.4226381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006470212024715474,"score_gpt":0.212534285859925,"score_spread":0.2060640738352095,"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."}}