{"id":"W3084189430","doi":"10.1162/qss_a_00086","title":"Using web content analysis to create innovation indicators—What do we really measure?","year":2020,"lang":"en","type":"article","venue":"Quantitative Science Studies","topic":"Web visibility and informetrics","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Confirmatory factor analysis; Content analysis; Measure (data warehouse); Business; Government (linguistics); Computer science; Knowledge management; Marketing; Data mining; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01805414,0.0007497711,0.001009541,0.02366591,0.0009398902,0.005997404,0.001013761,0.001092962,0.001600544],"category_scores_gemma":[0.1133585,0.0003355252,0.0007158222,0.02224492,0.001924593,0.01010122,0.001606181,0.001222781,0.001076805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00357341,"about_ca_system_score_gemma":0.005030294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01282385,"about_ca_topic_score_gemma":0.01135343,"domain_scores_codex":[0.9826311,0.006795541,0.001533212,0.0009014313,0.007268443,0.0008701697],"domain_scores_gemma":[0.8418081,0.09327052,0.01816013,0.006415201,0.03757911,0.002767046],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001875543,0.0003767605,0.5358268,0.001891071,0.0004753814,0.00009440101,0.008384641,0.001336354,0.003561874,0.01110875,0.00741412,0.4293424],"study_design_scores_gemma":[0.00009837466,0.0007344981,0.7861138,0.00435545,0.0007061151,0.000515483,0.03119592,0.02879217,0.01422348,0.03855364,0.09429447,0.0004166085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7318196,0.006130547,0.1854523,0.008333942,0.0007011026,0.002134126,0.008946563,0.001286336,0.05519544],"genre_scores_gemma":[0.8878089,0.002024126,0.1022735,0.00064138,0.0002600427,0.001747801,0.003230907,0.0002326455,0.001780832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9819459,"threshold_uncertainty_score":0.09548056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.372022180426349,"score_gpt":0.418371953123223,"score_spread":0.0463497726968739,"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."}}