{"id":"W3100463562","doi":"","title":"Spatial or Temporal Pooling Solves Wild Goose Chase","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Goose; Pooling; Computer science; Geography; Artificial intelligence; Ecology; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.001164969,0.0009961269,0.001915123,0.0004276965,0.0007268792,0.0009435908,0.001307126,0.001358935,0.004129932],"category_scores_gemma":[0.004027494,0.0004572579,0.0008870346,0.0006448759,0.00131193,0.002165168,0.003190973,0.001378475,0.0002850009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006017539,"about_ca_system_score_gemma":0.001466835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006380378,"about_ca_topic_score_gemma":0.002938542,"domain_scores_codex":[0.9993524,0.0001128741,0.00002588808,0.0001405146,0.00007010216,0.000298356],"domain_scores_gemma":[0.9978314,0.001237879,0.0002536373,0.0002359616,0.0001685133,0.0002726024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000952216,0.0003355569,0.004388935,0.0003329215,0.0002254654,0.001074039,0.0003098784,0.7495434,0.01013662,0.150457,0.009695173,0.07254869],"study_design_scores_gemma":[0.00003193183,0.00008344519,0.00034157,0.000007524771,0.00002544968,0.00007711172,0.00004937843,0.9483531,0.0007866082,0.0495747,0.0006572862,0.00001179508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2750182,0.0007687121,0.7110711,0.0007785141,0.0001492432,0.00008439684,0.0001952441,0.0004924297,0.01144216],"genre_scores_gemma":[0.9678761,0.0002047017,0.02602123,0.0001673552,0.00006726375,0.00005209461,0.0001461641,0.00008062817,0.005384597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006380378,"threshold_uncertainty_score":0.01381606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01437708404004409,"score_gpt":0.2289596362334385,"score_spread":0.2145825521933944,"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."}}