{"id":"W2742891567","doi":"10.1002/2017ea000297","title":"Factorial inferential grid grouping and representativeness analysis for a systematic selection of representative grids","year":2017,"lang":"en","type":"article","venue":"Earth and Space Science","topic":"Climate variability and models","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; Lamont-Doherty Earth Observatory, Columbia University; Higher Education Discipline Innovation Project","keywords":"Representativeness heuristic; Grid; Statistics; Selection (genetic algorithm); Normalization (sociology); Computer science; Environmental science; Econometrics; Mathematics; Geography; Data mining; Artificial intelligence; Geodesy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.03096691,0.0007229497,0.001339825,0.004110939,0.001293587,0.001954732,0.001136,0.0006705406,0.002266717],"category_scores_gemma":[0.1240684,0.000355565,0.001461649,0.003772796,0.001582088,0.001534896,0.001818213,0.0008610012,0.0002370686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009787285,"about_ca_system_score_gemma":0.002199959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003452175,"about_ca_topic_score_gemma":0.003125601,"domain_scores_codex":[0.9712886,0.02026249,0.001715072,0.003573588,0.002654162,0.0005060408],"domain_scores_gemma":[0.8849977,0.09070002,0.00559931,0.009828187,0.008186634,0.0006881987],"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":[0.001347539,0.0004025742,0.138129,0.00114153,0.0015231,0.0007004813,0.004902777,0.1172426,0.01069812,0.07727112,0.006878024,0.639763],"study_design_scores_gemma":[0.0002720063,0.0006664699,0.05627108,0.0001878134,0.0004429641,0.000228528,0.001822532,0.8314323,0.007656033,0.09114692,0.009727721,0.000145549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05988198,0.0001047874,0.9377509,0.00008213491,0.00002470867,0.0004583705,0.0003122862,0.0005940427,0.0007907569],"genre_scores_gemma":[0.3829194,0.00004101287,0.6149995,0.00004991772,0.00002169704,0.00102329,0.0006576436,0.0000983718,0.0001892302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03096691,"threshold_uncertainty_score":0.1637706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02999512618485126,"score_gpt":0.3125831371979763,"score_spread":0.282588011013125,"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."}}