{"id":"W6939648801","doi":"10.6084/m9.figshare.16869881","title":"Additional file 2 of Improve hot region prediction by analyzing different machine learning algorithms","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Hot spot (computer programming); Feature (linguistics); Pattern recognition (psychology); Support vector machine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001416477,0.001443148,0.001265945,0.00184676,0.0008056255,0.001712982,0.002090268,0.001443857,0.7429436],"category_scores_gemma":[0.01515683,0.0006184233,0.001408133,0.002550732,0.0002861163,0.001856979,0.001101291,0.001156688,0.1997418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000792663,"about_ca_system_score_gemma":0.001317881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004204353,"about_ca_topic_score_gemma":0.009141812,"domain_scores_codex":[0.9993191,0.0001080513,0.00007992698,0.0002294107,0.00017267,0.00009086796],"domain_scores_gemma":[0.9890029,0.008221232,0.0003835334,0.0008938948,0.00125886,0.0002395411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004275528,0.00009616841,0.002076924,0.001879111,0.00007203704,0.00007074702,0.00004139597,0.001067619,0.0004951305,0.0005259202,0.9838527,0.009394704],"study_design_scores_gemma":[0.005758673,0.000400658,0.02678728,0.001570094,0.0003870817,0.0005629014,0.0003763726,0.01534791,0.006459417,0.01747663,0.9245849,0.0002879415],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003677203,0.00003214657,0.001070949,0.00008952984,0.00003994609,0.00005038413,0.9950016,0.002640966,0.0007066735],"genre_scores_gemma":[0.007065953,0.0000758904,0.008543837,0.0003509478,0.00007918711,0.0007446298,0.9748082,0.003459066,0.00487218],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7429436,"threshold_uncertainty_score":0.3666596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01606937045931825,"score_gpt":0.1933513208511648,"score_spread":0.1772819503918466,"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."}}