{"id":"W2979505351","doi":"10.1177/1069072719879910","title":"We Can Do That? Technological Advances in Interest Assessment","year":2019,"lang":"en","type":"article","venue":"Journal of Career Assessment","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Data science; Computer science; Psychology","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":[0.06717401,0.001182953,0.001321713,0.003966002,0.002081304,0.01084351,0.002580963,0.003323965,0.009107288],"category_scores_gemma":[0.2647616,0.0006620204,0.00114419,0.003621347,0.008213421,0.02694765,0.005404439,0.009760215,0.007800942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002458264,"about_ca_system_score_gemma":0.005550493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002299897,"about_ca_topic_score_gemma":0.003328932,"domain_scores_codex":[0.9496072,0.03457746,0.002995714,0.002732615,0.008985809,0.001101193],"domain_scores_gemma":[0.8349481,0.1071036,0.01199984,0.01368305,0.02625597,0.00600939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002464195,0.0004671759,0.03496201,0.001257589,0.0002247236,0.0001737539,0.007203264,0.0007651338,0.0009834827,0.1253159,0.06916082,0.7592396],"study_design_scores_gemma":[0.0001090484,0.000676784,0.01848151,0.005536905,0.0002265732,0.0008477467,0.01456496,0.004348398,0.002922708,0.5502098,0.4016786,0.0003969482],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0346997,0.06042878,0.2828804,0.5467221,0.00765373,0.0007003188,0.001048265,0.001920447,0.06394631],"genre_scores_gemma":[0.3465403,0.05941092,0.4719979,0.09281476,0.006129752,0.001639501,0.0008347249,0.0008996646,0.01973256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06717401,"threshold_uncertainty_score":0.3552544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4444227929367293,"score_gpt":0.5173520996052661,"score_spread":0.07292930666853681,"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."}}