{"id":"W7038080468","doi":"","title":"Give A Damn Vancouver is giving back and giving a damn","year":2023,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Action (physics); Clothing; Subject (documents)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001222873,0.001007,0.0008886805,0.001823933,0.003134782,0.005958453,0.0009545475,0.002449583,0.7608079],"category_scores_gemma":[0.005387043,0.0006119143,0.0006290348,0.001343068,0.0006641533,0.002910459,0.002687767,0.003316046,0.6502109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002639616,"about_ca_system_score_gemma":0.003537093,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03084056,"about_ca_topic_score_gemma":0.112878,"domain_scores_codex":[0.9989059,0.0001077404,0.00002844181,0.0001421541,0.0006547002,0.0001610489],"domain_scores_gemma":[0.996066,0.0002611521,0.00007333037,0.0002234281,0.001701275,0.001674685],"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":[0.00001303097,0.00001047309,0.00002608813,0.00001546476,7.314922e-7,0.00001098536,0.000009733029,0.00002083566,0.00003758199,0.0005838629,0.9834815,0.01578971],"study_design_scores_gemma":[0.000003542666,0.000006296968,0.0001238814,0.00001823953,0.000001071265,0.00001144857,0.0000245989,0.00003098096,0.0000463613,0.0004368601,0.9992923,0.000004434587],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000451038,0.002170567,0.001293062,0.01298525,0.01581662,0.0001302068,0.004713287,0.00241381,0.9600262],"genre_scores_gemma":[0.0003585845,0.0001869437,0.0002087346,0.0004723653,0.000209359,0.000009155953,0.0003545968,0.0004042413,0.9977961],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9691594,"threshold_uncertainty_score":0.3411785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006761183630578677,"score_gpt":0.1893028341339123,"score_spread":0.1825416505033337,"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."}}