{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006772772,0.002135563,0.002266563,0.005569579,0.001252197,0.006693789,0.004708413,0.00291607,0.3219898],"category_scores_gemma":[0.04465275,0.001598329,0.002231117,0.007768188,0.0008340894,0.003627509,0.003814829,0.004754559,0.3986407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001766415,"about_ca_system_score_gemma":0.005414843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009170104,"about_ca_topic_score_gemma":0.04749088,"domain_scores_codex":[0.996922,0.0006349557,0.0005043861,0.0007719102,0.0008683692,0.0002984538],"domain_scores_gemma":[0.9793938,0.006892242,0.0007304433,0.004868194,0.005947188,0.002168172],"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":[0.00001082092,0.00001226794,0.0001622309,0.0001252223,0.000008431751,0.000003157402,0.000005089787,0.00005964328,0.00003233013,0.0001926554,0.997067,0.002321098],"study_design_scores_gemma":[0.0002104742,0.00001433564,0.0007196395,0.0002077446,0.00001867084,0.00002428003,0.00003030391,0.0008179067,0.0003032913,0.003107414,0.9945163,0.00002956862],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000188268,0.0001545192,0.00350278,0.0008222837,0.0006323035,0.0002396761,0.982694,0.005947839,0.005818388],"genre_scores_gemma":[0.0009437885,0.0002374413,0.0171879,0.001230626,0.0001760552,0.001277383,0.9667516,0.002756406,0.009438911],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3219898,"threshold_uncertainty_score":0.9670992,"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."}}