{"id":"W3200406703","doi":"10.3897/biss.5.74372","title":"Data Standards for the Phenology of Plant Specimens","year":2021,"lang":"en","type":"article","venue":"Biodiversity Information Science and Standards","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Science Foundation","keywords":"Phenology; Herbarium; Digitization; Computer science; Database; Geography; Ecology; 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":[],"consensus_categories":[],"category_scores_codex":[0.01942217,0.0009743655,0.0008263888,0.01090769,0.002245995,0.00476677,0.003473846,0.002219163,0.0164058],"category_scores_gemma":[0.05638659,0.0008156438,0.001351346,0.009870442,0.001294677,0.007258805,0.004798791,0.003870446,0.01580159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003646318,"about_ca_system_score_gemma":0.008285699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02188511,"about_ca_topic_score_gemma":0.02006998,"domain_scores_codex":[0.9851414,0.002276246,0.004882361,0.002034166,0.005050872,0.000614917],"domain_scores_gemma":[0.9172652,0.01679698,0.006845701,0.02602502,0.0298013,0.003265673],"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":[0.0005019243,0.0003720731,0.02673024,0.003667962,0.000144935,0.000366871,0.004452037,0.003679759,0.02342765,0.1307017,0.5449619,0.2609932],"study_design_scores_gemma":[0.00003065513,0.00003835541,0.01267891,0.000627134,0.00002882897,0.00012473,0.0004591023,0.00110001,0.003247228,0.01386576,0.9677207,0.00007855711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01371744,0.001021985,0.3686001,0.003632125,0.002105046,0.004033948,0.5007804,0.02036844,0.08574057],"genre_scores_gemma":[0.024522,0.001168912,0.2389148,0.002074435,0.0002843016,0.005627383,0.7049877,0.005939541,0.01648094],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02188511,"threshold_uncertainty_score":0.1027155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05637819301971513,"score_gpt":0.2837233119668771,"score_spread":0.227345118947162,"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."}}