{"id":"W2044744617","doi":"10.5558/tfc80384-3","title":"Approaches to setting forestry research priorities: Considering the benefits of reducing uncertainty","year":2004,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia; Agriculture Food and Rural Development; University of Alberta","funders":"","keywords":"Context (archaeology); Selection (genetic algorithm); Value (mathematics); Value of information; Management science; Computer science; Risk analysis (engineering); Environmental resource management; Data science; Business; Economics; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3356694,0.00191864,0.003543125,0.01413058,0.009034612,0.02308372,0.006588627,0.007527622,0.003756052],"category_scores_gemma":[0.4619593,0.001682577,0.002185301,0.0107422,0.01967563,0.02211336,0.0177829,0.008774695,0.0005409497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01906198,"about_ca_system_score_gemma":0.02970414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006922584,"about_ca_topic_score_gemma":0.01236462,"domain_scores_codex":[0.6180211,0.3230552,0.01142058,0.007040159,0.0350351,0.005427952],"domain_scores_gemma":[0.2714548,0.665983,0.02111383,0.01248808,0.02446906,0.004491278],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000361197,0.0001826317,0.00971739,0.00488142,0.0009039472,0.0006159422,0.02957063,0.03111161,0.0007198427,0.5395969,0.01080609,0.3715324],"study_design_scores_gemma":[0.0001217124,0.0001738192,0.002605259,0.003383967,0.0001970462,0.0001886086,0.01256401,0.009610481,0.0005701014,0.9246811,0.04569423,0.0002096246],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02713417,0.0196379,0.6839649,0.2200392,0.001732521,0.001815294,0.0003075786,0.0002559623,0.0451125],"genre_scores_gemma":[0.5579743,0.01293883,0.4063109,0.01318434,0.002449816,0.004819667,0.0001802224,0.000140737,0.00200111],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6643306,"threshold_uncertainty_score":0.8192379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1026286477397648,"score_gpt":0.2970500270605684,"score_spread":0.1944213793208037,"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."}}