{"id":"W4235267710","doi":"10.17975/sfj-2019-001","title":"2019 National High School Big Data Challenge: Big Data de Terre","year":2019,"lang":"en","type":"article","venue":"STEM Fellowship Journal","topic":"Big Data Technologies and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Data science; Political science; Computer science; Data mining","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":["open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006561758,0.0002285219,0.0003429942,0.0004006583,0.0004111144,0.001026893,0.0122636,0.0002428075,0.0007814754],"category_scores_gemma":[0.001696942,0.0001663078,0.00007363725,0.0008250395,0.0001386962,0.001294925,0.003828895,0.0009668125,0.005081515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001248447,"about_ca_system_score_gemma":0.0008271021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006184378,"about_ca_topic_score_gemma":0.0001401655,"domain_scores_codex":[0.9951769,0.0001911857,0.0008867643,0.001022084,0.002188509,0.0005346324],"domain_scores_gemma":[0.992753,0.0007016413,0.0005707771,0.005248374,0.0004177009,0.0003085596],"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":[0.0000202822,0.0001004511,0.005174752,0.000005307425,0.00004921596,0.00001741507,0.0000316755,0.00002728397,0.0004170801,0.002916422,0.6675399,0.3237002],"study_design_scores_gemma":[0.0007636606,0.00007469145,0.01145475,0.0000614194,0.00002630231,0.0003159038,0.001818758,0.002449873,0.00007830602,0.04546244,0.9371389,0.0003549565],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5441433,0.01417629,0.09832662,0.2109593,0.02744626,0.003100003,0.03086371,0.001118502,0.06986601],"genre_scores_gemma":[0.9854913,0.0008011127,0.003345348,0.0005767116,0.002394525,0.000007981056,0.0005756533,0.00003120149,0.006776144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.441348,"threshold_uncertainty_score":0.9956931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5394255743286756,"score_gpt":0.4134806470450783,"score_spread":0.1259449272835972,"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."}}