{"id":"W4206043242","doi":"10.3410/f.739734024.793588027","title":"Faculty Opinions recommendation of A practical guide to selecting models for exploration, inference, and prediction in ecology.","year":2021,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Inference; Ecology; Computer science; Management science; Data science; Engineering; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00265699,0.000382624,0.0008775733,0.0006703466,0.0002014332,0.0003128209,0.001449678,0.0005178985,0.00003387539],"category_scores_gemma":[0.02271595,0.000282677,0.0002605246,0.003856251,0.0001176427,0.001810961,0.0009605915,0.0007139221,0.00000774959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001546812,"about_ca_system_score_gemma":0.001067182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005243222,"about_ca_topic_score_gemma":0.00007722715,"domain_scores_codex":[0.9952331,0.0005982174,0.001875471,0.0009498478,0.001001155,0.00034225],"domain_scores_gemma":[0.9892172,0.0005359331,0.001280989,0.00144256,0.007262997,0.0002603191],"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":[0.000006181935,0.0002501348,0.00001119746,0.001912947,0.00007836395,2.145432e-7,0.0001758928,0.000007518015,0.00000101328,0.001723156,0.9940173,0.001816053],"study_design_scores_gemma":[0.0004648014,0.0001393895,0.0004554084,0.004017641,0.0001054039,0.00002433958,0.00004118921,0.003669859,0.000008965331,0.0002531965,0.9905862,0.0002335869],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.973705e-7,0.0001464324,0.04386024,0.2054603,0.0004042902,0.001244669,0.7488405,0.00002745412,0.00001591361],"genre_scores_gemma":[0.000005998779,0.0001815466,0.03795253,0.00349876,0.0001287216,0.0006765607,0.9573056,0.00001316718,0.0002370883],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2084652,"threshold_uncertainty_score":0.9999626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06171480742003457,"score_gpt":0.4047019605555237,"score_spread":0.3429871531354891,"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."}}