{"id":"W7054890031","doi":"","title":"Challenges in modeling the abundance of 105 tree species in eastern North America for climate change research","year":2011,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Atomic and Subatomic Physics Research","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère des Ressources Naturelles et de la Faune","keywords":"Edaphic; Abundance (ecology); Relative species abundance; Climate change; Species distribution; Forest management; Generalized linear model; Tree (set theory); Environmental change","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001355007,0.0005056785,0.000858715,0.0005619692,0.0004706792,0.00005911192,0.001202494,0.0002296991,0.00006982122],"category_scores_gemma":[0.00007745014,0.0004462368,0.0003080252,0.0007113178,0.0001420245,0.000574761,0.0002650759,0.001865695,0.00008502159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002930566,"about_ca_system_score_gemma":0.0001137367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001657297,"about_ca_topic_score_gemma":0.005711086,"domain_scores_codex":[0.995872,0.00037935,0.0008761151,0.0009209539,0.0007696972,0.001181878],"domain_scores_gemma":[0.997771,0.0004425876,0.0003660254,0.000801313,0.000478276,0.0001408411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005497457,0.0004222361,0.002393904,0.0005234241,0.0001042075,0.000005354681,0.0006664993,0.00009378396,0.0004382884,0.1116772,8.83797e-7,0.8831245],"study_design_scores_gemma":[0.01048957,0.0009003239,0.02728572,0.007197813,0.0002778995,0.000003110982,0.1047565,0.1303841,0.01383195,0.6615899,0.03727785,0.006005283],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8848311,0.0007382425,0.000003589126,0.00002673614,0.0001748414,0.001477888,0.001157228,0.00002124042,0.1115691],"genre_scores_gemma":[0.9951455,0.001666862,0.0000509716,0.0000104926,0.0001342504,0.00100672,0.0005531879,0.0001358243,0.001296207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8771192,"threshold_uncertainty_score":0.999799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1961684877251748,"score_gpt":0.3468476777825384,"score_spread":0.1506791900573637,"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."}}