{"id":"W4398492753","doi":"10.7910/dvn/28075/yukqmw","title":"events.2000.20150313082808.tab.zip","year":2015,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Geography; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007179404,0.001631618,0.001048575,0.003866338,0.0005602548,0.002694903,0.001916561,0.001549814,0.1541826],"category_scores_gemma":[0.004543324,0.0007665631,0.0007144173,0.007127058,0.0003235558,0.001242559,0.001426752,0.001391324,0.1723172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001471986,"about_ca_system_score_gemma":0.00142742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02233785,"about_ca_topic_score_gemma":0.03468482,"domain_scores_codex":[0.9994538,0.00006021585,0.00008032007,0.0001628556,0.0001301311,0.0001127009],"domain_scores_gemma":[0.9984232,0.0003675435,0.0003263703,0.0003092355,0.0003571588,0.000216502],"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":[0.00004702106,0.00001344841,0.0008531744,0.0002285481,0.0000119102,0.00001405081,0.00001266314,0.0001786945,0.00004024641,0.0005046296,0.9967289,0.001366623],"study_design_scores_gemma":[0.0003597998,0.00002098773,0.007112201,0.0002557097,0.00002388652,0.00005566216,0.00006082703,0.0004602827,0.0002832506,0.001364734,0.9899763,0.00002636775],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001034728,0.00003230013,0.00002964544,0.00004148317,0.00001453464,0.000004493352,0.9989492,0.0001538093,0.0006710123],"genre_scores_gemma":[0.0005331793,0.00005305701,0.00008547233,0.00003944468,0.00001281491,0.0000290108,0.9979967,0.00005488193,0.001195393],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8458174,"threshold_uncertainty_score":0.5157921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05442505987154198,"score_gpt":0.22746582249306,"score_spread":0.173040762621518,"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."}}