{"id":"W1503955258","doi":"10.18438/b8630n","title":"A Virtual Standoff – Using Q Methodology to Analyze Virtual Reference","year":2007,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Viewpoints; Computer science; Variety (cybernetics); Factor (programming language); Task (project management); Reference model; Convergence (economics); Information retrieval; Artificial intelligence; Software engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04262108,0.0006094694,0.0007916503,0.007625723,0.001944945,0.002877906,0.001062114,0.000549635,0.007598002],"category_scores_gemma":[0.104431,0.000372321,0.0006612435,0.007346504,0.002958987,0.003613353,0.003011786,0.0008831376,0.0009247419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482754,"about_ca_system_score_gemma":0.002986572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002459216,"about_ca_topic_score_gemma":0.002132293,"domain_scores_codex":[0.947467,0.04283724,0.002141023,0.001774813,0.005091094,0.0006888247],"domain_scores_gemma":[0.8875847,0.0809278,0.006186773,0.006042201,0.01858714,0.0006713546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001060448,0.001046936,0.1281766,0.001500729,0.0001200572,0.0006551479,0.1369206,0.003463414,0.01157683,0.08795098,0.008001174,0.619527],"study_design_scores_gemma":[0.0006808691,0.006960243,0.2870426,0.001753987,0.0001602024,0.001035275,0.2730382,0.1160182,0.02194298,0.1942687,0.09661688,0.0004817111],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4662548,0.0001706093,0.5058447,0.000739503,0.00008784833,0.006759514,0.0007959194,0.0003690478,0.01897814],"genre_scores_gemma":[0.6653252,0.00007230704,0.32423,0.0002020698,0.00002507597,0.007441842,0.0003614934,0.00007668632,0.002265307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04262108,"threshold_uncertainty_score":0.2254045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07289448728542963,"score_gpt":0.3719500216817122,"score_spread":0.2990555343962826,"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."}}