{"id":"W2406745441","doi":"","title":"Analyzing open data from the city of Montreal","year":2015,"lang":"en","type":"article","venue":"International Conference on Machine Learning","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Open data; Computer science; Context (archaeology); Data science; World Wide Web; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0005871278,0.00008151814,0.0001074489,0.00003547364,0.00008907314,0.000432956,0.006340155,0.00002111688,0.00009495296],"category_scores_gemma":[0.0003429186,0.00005892809,0.00001760892,0.0001342773,0.00003545637,0.0005901197,0.002798649,0.000241314,0.00004807799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001942114,"about_ca_system_score_gemma":0.0001011303,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0104858,"about_ca_topic_score_gemma":0.0005052442,"domain_scores_codex":[0.9990058,0.00008359161,0.0001875522,0.0003454373,0.0002858287,0.00009181012],"domain_scores_gemma":[0.9986323,0.0001876271,0.0001701768,0.0007873936,0.000166135,0.0000564189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005080097,0.00021914,0.09043363,0.000001697194,0.0001874364,0.00001008826,0.001719668,0.001221971,0.0003605481,0.3368489,0.006027878,0.5629183],"study_design_scores_gemma":[0.0002868879,0.00003667875,0.0168754,0.00002807618,0.000005296465,0.000001887597,0.00009932077,0.9624803,0.00004614818,0.007261979,0.01279499,0.00008302078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0314481,0.0001009658,0.8667637,0.01950971,0.0004729611,0.0002281042,0.0006599092,0.000119287,0.08069731],"genre_scores_gemma":[0.9683014,0.00001698702,0.03035462,0.0001642293,0.0000893187,0.000007200419,0.0005558996,0.000004748581,0.0005056715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9612584,"threshold_uncertainty_score":0.999036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1999673731469835,"score_gpt":0.3826793677675259,"score_spread":0.1827119946205424,"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."}}