{"id":"W2783877980","doi":"10.1002/wsb.847","title":"Wildlife biology, big data, and reproducible research","year":2018,"lang":"en","type":"article","venue":"Wildlife Society Bulletin","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Memorial University of Newfoundland","funders":"","keywords":"Wildlife; Scripting language; Data science; Best practice; Field (mathematics); Process (computing); Quality (philosophy); Computer science; Inefficiency; Data quality; Ecology; Biology; Political science; Business; Marketing","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002453245,0.0001542868,0.0001624523,0.00001702316,0.0006679412,0.00007913317,0.0006482041,0.0001588098,0.04386847],"category_scores_gemma":[0.0003925428,0.0001402712,0.00005828301,0.0004173989,0.00246823,0.00006622994,0.001871093,0.0002939346,0.009185025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002063701,"about_ca_system_score_gemma":0.00001962976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006323057,"about_ca_topic_score_gemma":0.0001031448,"domain_scores_codex":[0.997606,0.0001456113,0.0002195065,0.001042432,0.0003818761,0.000604535],"domain_scores_gemma":[0.9983162,0.0001029008,0.00006045464,0.001278376,0.0000453701,0.0001966444],"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":[0.00001000941,0.00005864223,0.0315464,0.000005998218,0.00001183237,7.600906e-7,0.000424584,6.706551e-8,0.0007986577,0.000335592,0.9644257,0.002381701],"study_design_scores_gemma":[0.0002865999,0.00009485194,0.01856242,0.000007928447,0.000006489122,0.000007165682,0.003438296,0.00004739537,0.000133701,0.0001295593,0.9771166,0.0001689961],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7045305,0.0006583736,0.0002405315,0.1409179,0.001068473,0.0007221731,0.0006263526,0.0003160135,0.1509196],"genre_scores_gemma":[0.9446003,0.002515679,0.001935584,0.03586745,0.002617539,0.00006875859,0.0007371173,0.00007174176,0.01158583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2400698,"threshold_uncertainty_score":0.9915864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1432863690438766,"score_gpt":0.3486182328963437,"score_spread":0.2053318638524672,"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."}}