{"id":"W4386699790","doi":"10.32920/24135144.v1","title":"Pollen sleuthing for terrestrial plant surveys: Locating plant populations by exploiting pollen movement","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pollen; Population; Biology; Pollen source; Botany; Horticulture; Pollination; Pollinator","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004855592,0.0003429142,0.0003015872,0.0006778942,0.0003120337,0.0003308743,0.0006347219,0.0003880149,0.002013806],"category_scores_gemma":[0.0008413875,0.0002415566,0.0002247727,0.000406615,0.0003622071,0.0004513095,0.0005026868,0.0003716773,0.0006574907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002774629,"about_ca_system_score_gemma":0.0002987427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002201768,"about_ca_topic_score_gemma":0.006483483,"domain_scores_codex":[0.9997419,0.00008058494,0.00001080182,0.00009479203,0.00005465024,0.00001719302],"domain_scores_gemma":[0.9995329,0.0001508416,0.0001326108,0.00008897323,0.0000428589,0.00005179744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003131382,0.0001071515,0.1260578,0.0003646788,0.0000736788,0.0003840086,0.0003597881,0.006124537,0.6062862,0.0008735004,0.001265445,0.2577899],"study_design_scores_gemma":[0.000114873,0.001835649,0.6151918,0.0001919921,0.0001558648,0.002910217,0.0008713749,0.1658717,0.194685,0.002244841,0.01577817,0.0001485265],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6938647,0.0005913207,0.2973929,0.0002147211,0.00003323171,0.0002818039,0.0006506817,0.001014809,0.005955765],"genre_scores_gemma":[0.751039,0.0002523743,0.2464888,0.0001286196,0.0000170907,0.0002421162,0.0002802122,0.00006806575,0.001483734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002201768,"threshold_uncertainty_score":0.006736815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3126603405096852,"score_gpt":0.2887489736907011,"score_spread":0.02391136681898409,"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."}}