{"id":"W2117651860","doi":"10.1088/0031-9120/48/5/670","title":"Molasses or crowds: making sense of the Higgs boson with two popular analogies","year":2013,"lang":"en","type":"article","venue":"Physics Education","topic":"Particle physics theoretical and experimental studies","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Higgs boson; Large Hadron Collider; Particle physics; Meaning (existential); Crowds; Physics; Higgs mechanism; Phenomenon; Higgs field; Theoretical physics; Epistemology; Computer science; Philosophy; Quantum mechanics","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":[0.00277383,0.000757752,0.0005603984,0.002463602,0.003278115,0.006862754,0.001866988,0.004120369,0.007062338],"category_scores_gemma":[0.01350963,0.0003619137,0.000681689,0.001582109,0.02859473,0.02208283,0.006256334,0.004438316,0.0008840464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001588443,"about_ca_system_score_gemma":0.0009397764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001881244,"about_ca_topic_score_gemma":0.001277512,"domain_scores_codex":[0.996726,0.001630075,0.0001565398,0.0006548546,0.0006334062,0.0001991172],"domain_scores_gemma":[0.9945207,0.003630075,0.0005422945,0.000619798,0.0003685101,0.0003187046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004903772,0.00002080924,0.001036381,0.000136372,0.00001931674,0.0003401433,0.015036,0.0004041679,0.0002696041,0.9565041,0.005307074,0.02087703],"study_design_scores_gemma":[0.00001887844,0.00001714687,0.0006670592,0.0001282906,0.00001165349,0.0003069358,0.004939246,0.001091612,0.0001744598,0.9415288,0.05108729,0.00002867846],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1171344,0.03410658,0.1522822,0.188524,0.003439809,0.0001674615,0.0004361339,0.00051226,0.5033971],"genre_scores_gemma":[0.9331157,0.009589038,0.0250891,0.01223586,0.001596284,0.0001774116,0.0001763141,0.0001354678,0.01788502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007062338,"threshold_uncertainty_score":0.02362591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764048750997881,"score_gpt":0.3004289649064795,"score_spread":0.2827884773965007,"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."}}